Serum Metabolomic Signatures Indicate Oxidative Membrane Lipid Remodeling in β-Thalassemia

<b>Background/Objectives</b>: Oxidative stress and iron overload remodel erythrocyte membranes in β-thalassemia, but their systemic metabolic correlates are not well defined. We applied untargeted metabolomics to identify serum biomarkers reflecting these pathophysiological processes. <b>Methods</b>: Thirty-one adults with β-thalassemia [18 transfusion-dependent (TDT), 13 non-transfusion-dependent (NTD)] and 8 age/sex-matched healthy controls were studied. Fasting serum was profiled using untargeted UHPLC–Orbitrap MS. Multivariate modeling (SIMCA-P) and FDR-controlled univariate statistics identified discriminant features, followed by pathway enrichment analysis. Associations with clinical variables (chelation regimen, ferritin, cardiac MRI T2*, and liver iron concentration) were examined. <b>Results</b>: A total of 183 metabolites were detected; versus controls, 124 were decreased, 54 increased, and 5 remained unchanged in patients. Key discriminants included lysophosphatidylcholines (LysoPC 18:1, 18:3), polyunsaturated fatty acid (PUFA)-bearing phosphatidylcholines (PC 20:4/18:0, PC 18:0/20:4), conjugated bile acids (glycocholic acid, glycochenodeoxycholic acid, and glycoursodeoxycholic acid), and bilirubin. Pathway analysis revealed significant enrichment (FDR-corrected) in linoleic acid metabolism (q = 0.024, impact = 1.000) and arachidonic acid metabolism (q = 0.022, impact = 0.433), with supportive nominal signals from glycerophospholipid (impact = 0.401) and porphyrin/heme (impact = 0.242) pathways. No significant metabolic differences were observed between TD and NTD patients. <b>Conclusions</b>: β-thalassemia serum metabolomics reflects oxidative membrane lipid remodeling with a prominent PLA₂/LysoPC–arachidonic axis and evidence of heme turnover and altered bile-acid signaling. These data propose a practical biomarker panel-LysoPCs, arachidonic acid-enriched PCs, and conjugated bile acids-warranting targeted validation alongside conventional clinical parameters for disease monitoring and therapeutic assessment.