NMR-Based Clinical Metabolomics Reveals Distinctive Metabolic Signatures in Systemic Sclerosis and Systemic Lupus Erythematosus

Systemic sclerosis (SSc) and systemic lupus erythematosus (SLE) are chronic and complex autoimmune diseases with shared clinical features complicating differential disease diagnosis. Despite similarities, they exhibit distinct pathophysiological mechanisms and disease progression. This study is an attempt to investigate disease-specific metabolic alterations and identify potential biomarkers for differential diagnosis using a nuclear magnetic resonance (NMR)-based serum metabolomics approach. 1D ¹H Carr-Purcell-Meiboom-Gill (CPMG) NMR spectra were recorded, and a total of 35 serum metabolites were quantified using CHENOMX software across SSc, SLE, and healthy control (HC) groups. Multivariate and univariate statistical analyses revealed significant metabolic distinctions between the diseases. SLE is primarily characterized by disruptions in glycolysis, the tricarboxylic acid (TCA) cycle, and oxidative stress, indicating compromised energy metabolism and immune-mediated mitochondrial dysfunction. In contrast, SSc showed distinct perturbations in inositol and amino acid metabolism linked to fibrosis and endothelial dysfunction. Significantly elevated levels of acetate emerged as a key discriminatory metabolite in SSc patients, implying a shift towards enhanced fatty acid oxidation in SSc, potentially fueling fibrotic processes and contributing to the energy demands of chronic inflammation. Specific metabolic ratios (with acetate as the numerator) demonstrated high accuracy in distinguishing SSc from SLE and HC, highlighting their potential as diagnostic biomarkers; including multivariate and multiclass ROC, supported the diagnostic relevance of these markers. The study underscores the metabolic heterogeneity of SLE and SSc, offering new insights and a deeper understanding into their distinct pathological mechanisms and supporting the development of biomarker-based strategies for improved diagnosis, classification, and personalized therapeutic approaches.