Metabolites

Background/Objectives: 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. Methods: 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. Results: 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. Conclusions: 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.

Background: The presence of metabolic syndrome (MetS) in children predisposes them to steatotic liver disease, with or without liver enzyme alterations. Early diagnosis of the degree of liver damage can stop the progression to more severe dysfunction. Objectives: This study aimed to establish the link between liver enzyme levels and triglyceride and cholesterol values in pediatric patients with obesity, grouped according to MetS status and metabolic dysfunction-associated fatty liver disease (MAFLD). Methods: The retrospective observational study included 261 pediatric patients aged between 0 and 18 years diagnosed with obesity, MetS, and MAFLD. Before initiating the study, approval was obtained from the hospital’s Ethics Committee. The clinical and biochemical data were collected from the patients’ histories. Results: Alanine aminotransferase showed a significant positive correlation with triglyceride levels in the overall cohort, which became stronger in children with MetS and was strongest in those with ultrasonographically confirmed MAFLD. Similarly, aspartate aminotransferase demonstrated a weak positive correlation with triglycerides in the overall population, which increased in patients with MetS and became strong in children with MAFLD. Conclusions: In children with MetS and ultrasound-diagnosed MAFLD, liver enzymes showed progressively stronger positive correlations with triglyceride levels, indicating a close link between dyslipidemia and liver damage. Associations between liver enzymes and total cholesterol further support metabolic dysregulation, rather than body mass index alone, as a key driver of pediatric steatotic liver disease and highlight the value of targeted liver enzyme assessment in children with MetS or hypertriglyceridemia.

Background/Objectives: Autism spectrum disorder (ASD) is biologically heterogeneous, and immune-linked variation may be associated with differences in tryptophan–kynurenine pathway (KP) metabolism. Here, we report a targeted urinary profile of KP metabolites, NAD (nicotinamide adenine dinucleotide), and neopterin in a Bulgarian pediatric ASD cohort to describe within-cohort patterns and associations. Methods: Second-morning, acid-stabilized spot urine was collected from 73 children with ASD in Bulgaria (3–13 years; 57 males; 16 females). No contemporaneous neurotypical control group was enrolled; therefore, laboratory-provided reference limits are reported only as contextual benchmarks and are not interpreted as ASD-specific abnormalities. Tryptophan (TRP), kynurenine (KYN), kynurenic acid (KYNA), 3-hydroxykynurenine (3-HK), quinolinic acid (QUIN), NAD, and neopterin were quantified and derived indices were computed (KYN/TRP × 1000; QUIN/KYNA). Non-parametric statistics, Benjamini–Hochberg false discovery rate (FDR) correction, and Spearman correlation analyses were applied. Results: Neopterin was strongly associated with QUIN and KYN in creatinine-normalized data (QUIN: ρ = 0.59, q36 = 2.64 × 10⁻⁷; KYN: ρ = 0.54, q36 = 3.69 × 10⁻⁶); these associations persisted when reconstructed as absolute concentrations (e.g., QUIN_abs: ρ = 0.68, q36 = 2.69 × 10⁻¹⁰) and after partial Spearman correlation controlling for spot creatinine (partial ρ = 0.46, q = 2.52 × 10⁻⁴). One NAD value was <LOQ and was imputed as ½LOQ; sensitivity analyses did not materially change inference. Conclusions: In this ASD-only cross-sectional dataset, urinary neopterin levels co-varied with urinary KYN and QUIN and with KP indices. Clinical interpretation and causal inference require controlled and longitudinal studies with richer covariate capture.