Accurately diagnosing mustard lung disease (MLD) presents a significant challenge due to its intricate nature and overlapping clinical features with other pulmonary conditions. A precise diagnosis is crucial for effective therapeutic management and optimizing patient care. Furthermore, understanding the metabolic shifts induced by sulfur mustard (SM) exposure is critical for elucidating the disease’s mechanisms and developing targeted interventions. This study employed an untargeted metabolomics and lipidomics profiling by liquid chromatography-mass spectrometry (LC-MS). We analyzed samples from MLD patients ( n = 39; 20 mild, 19 moderate severity) and a control group ( n = 14). We used multivariate/univariate statistical methods to identify distinguishing metabolites and lipids, and then performed pathway enrichment analysis to uncover the perturbed biochemical pathways. Our results demonstrated significant metabolic disruptions in MLD patients. We identified 16 metabolite panels capable of diagnosing mild MLD against controls, and 22 metabolite panels for moderate MLD versus controls (AUC > 0.85). Additionally, in comparison with the control group, four lipids were detected in the mild MLD group and five in the moderate MLD group ( p- value < 0.05). Our findings reveal unique metabolite and lipid profiles and widespread disturbances across various metabolic pathways, including amino acid, butyrate, propanoate metabolism, and carnitine synthesis, which differentiate MLD from controls. This research represents the first investigation into metabolomic and lipidomic signatures that discriminate MLD from control groups using LC-MS. Significant metabolites show promise as candidate biomarkers for MLD diagnosis or prognosis and offer valuable insights for further research into the disease’s pathological mechanisms, pending validation in larger prospective cohorts.
Gh. et al. (Fri,) studied this question.