¹H NMR-based metabolomic study of metabolic profiling for systemic lupus erythematosus

Abstract

Systemic lupus erythematosus (SLE) is a chronic inflammatory disease characterized by multi-system involvement, diverse clinical presentation, and alterations in circulating metabolites. In this study, a (1)H NMR spectroscopy-based metabolomics approach was applied to establish a human SLE serum metabolic profile. Serum samples were obtained from patients with SLE (n = 64), patients with rheumatoid arthritis (RA) (n = 30) and healthy controls (n = 35). The NOESYPR1D spectrum combined with multi-variate pattern recognition analysis was used to cluster the groups and establish a disease-specific metabolites phenotype. Principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) models were capable of distinguishing SLE or RA patients from healthy subjects. The OPLS-DA model was able to predict diagnosis of SLE with a sensitivity rate of 60.9% and a specificity rate of 97.1%. For diagnosing RA, the model has much higher sensitivity (96.7%) and specificity (91.4%). The SLE serum samples were characterized by reduced concentrations of valine, tyrosine, phenylalanine, lysine, isoleucine, histidine, glutamine, alanine, citrate, creatinine, creatine, pyruvate, high-density lipoprotein, cholesterol, glycerol, formate and increased concentrations of N-acetyl glycoprotein, very low-density lipoprotein and low-density lipoprotein in comparison with the control population. The results not only indicated that serum NMR-based metabolomic methods had sufficient sensitivity and specificity to distinguish SLE and RA from healthy controls, but also have the potential to be developed into a clinically useful diagnostic tool, and could also contribute to a further understanding of disease mechanisms.

Acute metabolic response of Portunus trituberculatus to Vibrio alginolyticus infection

“…Characterization of metabolomic differences between healthy and diseased states can improve our understanding of the mechanisms underlying pathological processes (Guma et al, 2016). Many successful applications of NMR-based metabolomics have been reported for a wide range of diseases such as schistosomiasis (Wu et al, 2010), systemic lupus erythematosus (Ouyang et al, 2011), osteoarthritis (Lamers et al, 2005), rheumatoid arthritis (Priori et al, 2015), and diabetes mellitus (Xu et al, 2012).…”

Biomarkers for systemic lupus erythematosus: an update

“…Metabolomics has become feasible with the use of new technologies, such as mass spectrometry (MS) and high-resolution proton nuclear magnetic resonance. The first metabolomic study utilizing nuclear magnetic resonance spectroscopy was performed on SLE serum, and found reductions in energy substrates, increased low-density lipoproteins and increased lactate [81]. Another metabolomic study in SLE was performed with liquid chromatography/MS and gas chromatography/MS platforms.…”

1H NMR-based Plasma Metabolic Profiling of Dairy Cows with Type I and Type II Ketosis

“…The δ5.5-9.0 region (dashed box) was magnified 10 times relative to the δ0.5-5.5 region for clarity. The samples K 1-15 , K 1-16 , K 2-8 , K [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16] , and C 8 were removed to achieve a better quality of spectrum and a better suppression effect of the water peak. The data were subsequently analyzed using multivariate statistics (PCA and OPLS-DA).…”

“…The discovery of disease biomarkers by 1H-NMR coupled to multivariate statistical analyses will provide novel ideas regarding disease pathogenesis and prevention strategies. Metabolomics has not only been used in metabolic profiles and pathogenesis of human diseases (e.g., liver cirrhosis, bladder cancer, diabetes, and lupus erythematosus) [11][12][13][14], but also in the description of pathological diseases, discovery of novel biomarkers, and elucidation of metabolic regulatory pathways. Studies have focused on the metabolomics of type I ketosis [15][16][17][18][19][20][21][22][23][24]; however, there are no studies on the metabolomics of type II ketosis.…”