DECONVOLUTION OF METABOLIC BIOMARKER SIGNATURES OF VERY EARLY DIAGNOSIS OF SYSTEMIC SCLEROSIS (VEDOSS) AND ESTABLISHED DISEASE: EXPLORATORY METABOLIC BIOMARKERS OF FAST PROGRESSORS.

Abstract

Introduction: Systemic sclerosis (SSc) is a complex autoimmune disease characterized by its asynchronous impact on multiple organs, resulting in highly variable fibrotic damage and elevated morbidity and mortality rates. Despite advancements in omics research shedding light on potential genes and proteins contributing to disease heterogeneity, effectively sub-stratifying individuals with rapidly progressing disease requiring urgent medical intervention remains a formidable challenge. In this study, we aim to elucidate previously underexplored metabolic serum biomarkers to identify individuals with rapid disease progression. Material(s) and Method(s): We compared the global metabolic profiles measured by high-performance chemical isotope labeling LC-MS (Dansyl-labeling) of the selected SSc serum samples from the ongoing SSc registry at the University of Leeds, including 33 VEDOSS, 20 progressing diffuse cutaneous SSc (pDcSSc), 27 stable DcSSc (sDcSSc), and 22 limited cutaneous SSc (LcSSc). All metabolites corresponding to each clinical subset of SSc were identified by IsoMS Pro 1.2.19 and NovaMT Metabolite Database v3.0 and classified according to a three-tier identification method. The significant metabolite pathways per each subset were analyzed by MetaboAnalyst 5.0. Result(s): We measured a total of n=7538 distinct metabolic features with 362, 672, and 708 metabolites significantly dysregulated in pDcSSc, sDcSSc, and LcSSc as compared to VEDOSS (nominal p-value less than or equal to 0.05), respectively. Along with the disease progression from VEDOSS to established SSc, "Arginine and proline metabolism" a putative potentiator of TGFbeta-induced production of matrix protein, was globally and the most significantly dysregulated across the disease subsets (nominal p-value less than or equal to 0.05). "Beta-Alanine metabolism" and "Histidine metabolism" were uniquely and significantly dysregulated in sDcSSc and LcSSc, respectively. Furthermore, we conducted binary classification analyses using baseline biomarkers, leading to the identification of 20 and 15 classified metabolic biomarkers associated with early disease progression in the lung (e.g., 4-Hydroxyphenylglyoxylic Acid and N-Acetyl-5-Hydroxyl-L-tryptophan) and skin (e.g., Dihydronaringenin-O-sulphate and Tryptophyl-Serine), respectively (rate/month for rapid progressor, mRSS >0.2; FVC <-0.5, AUC >0.7). Conclusion(s): These findings suggest that metabolic changes in serum samples from SSc patients are closely linked to clinical subsets, and some of these metabolic biomarkers show correlations with clinical manifestations such as skin and lung fibrosis. It is important to note that while our results are promising, further validation studies in an independent cohort are necessary to confirm the reliability and robustness of these metabolic biomarkers. Nonetheless, our findings hold the potential to contribute to the identification of individuals at risk of rapid disease progression in the context of SSc.