Background/Purpose:

Proton based Nuclear Magnetic Resonance (¹H NMR) can identify concentration of hundreds of small molecules in body fluids. A hypothesis-free approach was used to analyze metabolic perturbations in sera of Systemic Sclerosis (SSc) to identify potential biomarkers of the disease.

Methods:

Sera from 87 patients meeting ACR 1980 criteria for Systemic Sclerosis, and 40 age and sex similar controls, was analyzed using ¹H NMR spectroscopy coupled with multivariate statistical analysis.

Results:

There was clear distinction between SSc and healthy controls on Partial Least Square-Discriminate Analysis (PLS-DA) [R²= 0.98]. Several metabolites of discriminatory relevance were  identified, and further evaluated using analysis of variance (ANOVA) and Receiver Operator Curve (ROC) analysis. Methylamine, nitrosodimethylamine (NDMA), citrate and malonate were 4 metabolites that had maximum area under curve (AUC> 0.95) in distinguishing SSc from controls [Figure 2]. Methylamine and NDMA were uniformly elevated almost exclusively in SSc patients. Figure 3 shows Orthogonal PLS-DA of limited versus diffuse disease; or patients with or without interstitial lung disease (ILD).

Conclusion:

H¹ NMR based metabolomics identified metabolites that have high discriminate value for SSc. The potential of these molecules as biomarkers, or their possible roles in disease pathogenesis need to be explored.