Background: Autism spectrum disorder (ASD) is a developmental disorder characterized by deficits in social interaction, restricted interest and repetitive behavior. Oxidative stress in response to environmental exposure plays a role in virtually every human disease and represents a significant avenue of research into the etiology of ASD. The aim of this study was to explore the diagnostic utility of four urinary biomarkers of oxidative stress. Methods: One hundred and thirty-nine (139) children and adolescents with ASD (89% male, average age = 10.0 years, age range = 2.1 to 18.1 years) and 47 healthy children and adolescents (49% male, average age 9.2, age range = 2.5 to 20.8 years) were recruited for this study. Their urinary 8-OH-dG, 8-isoprostane, dityrosine and hexanoil-lisine were determined by using the ELISA method. Urinary creatinine was determined with the kinetic Jaffee reaction and was used to normalize all biochemical measurements. Non-parametric tests and support vector machines (SVM) with three different kernel functions (linear, radial, polynomial) were used to explore and optimize the multivariate prediction of an ASD diagnosis based on the collected biochemical measurements. The SVM models were first trained using data from a random subset of children and adolescents from the ASD group (n = 70, 90% male, average age = 9.7 years, age range = 2.1 to 17.8 years) and the control group (n = 24, 45.8% male, average age = 9.4 years, age range = 2.5 to 20.8 years) using bootstrapping, with additional synthetic minority over-sampling (SMOTE), which was utilized because of unbalanced data. The computed SVM models were then validated using the remaining data from children and adolescents from the ASD (n = 69, 88% male, average age = 10.2 years, age range = 4.3 to 18.1 years) and the control group (n = 23, 52.2% male, average age = 8.9 years, age range = 2.6 to 16.7 years). Results: Using a non-parametric test, we found a trend showing that the urinary 8-OH-dG concentration was lower in children with ASD compared to the control group (unadjusted p = 0.085). When all four biochemical measurements were combined using SVMs with a radial kernel function, we could predict an ASD diagnosis with a balanced accuracy of 73.4%, thereby accounting for an estimated 20.8% of variance (p < 0.001). The predictive accuracy expressed as the area under the curve (AUC) was solid (95% CI = 0.691–0.908). Using the validation data, we achieved significantly lower rates of classification accuracy as expressed by the balanced accuracy (60.1%), the AUC (95% CI = 0.502–0.781) and the percentage of explained variance (R² = 3.8%). Although the radial SVMs showed less predictive power using the validation data, they do, together with ratings of standardized SVM variable importance, provide some indication that urinary levels of 8-OH-dG and 8-isoprostane are predictive of an ASD diagnosis. Conclusions: Our results indicate that the examined urinary biomarkers in combination may differentiate children with ASD from healthy peers to a significant extent. However, the etiological importance of these findings is difficult to assesses, due to the high-dimensional nature of SVMs and a radial kernel function. Nonetheless, our results show that machine learning methods may provide significant insight into ASD and other disorders that could be related to oxidative stress.

Autism spectrum disorder (ASD) is a complex developmental disorder in which communication and behavior are affected. A number of studies have investigated potential biomarkers, including uremic toxins. The aim of our study was to determine uremic toxins in the urine of children with ASD (143) and compare the results with healthy children (48). Uremic toxins were determined with a validated high-performance liquid chromatography coupled to mass spectrometry (LC-MS/MS) method. We observed higher levels of p-cresyl sulphate (pCS) and indoxyl sulphate (IS) in the ASD group compared to the controls. Moreover, the toxin levels of trimethylamine N-oxide (TMAO), symmetric dimethylarginine (SDMA), and asymmetric dimethylarginine (ADMA) were lower in ASD patients. Similarly, for pCS and IS in children classified, according to the intensity of their symptoms, into mild, moderate, and severe, elevated levels of these compounds were observed. For mild severity of the disorder, elevated levels of TMAO and comparable levels of SDMA and ADMA for ASD children as compared to the controls were observed in the urine. For moderate severity of ASD, significantly elevated levels of TMAO but reduced levels of SDMA and ADMA were observed in the urine of ASD children as compared to the controls. When the results obtained for severe ASD severity were considered, reduced levels of TMAO and comparable levels of SDMA and ADMA were observed in ASD children.

Background: Immune dysregulation and gut dysbiosis are increasingly implicated in autism spectrum disorder (ASD), but compartment-specific intestinal cytokine profiles remain poorly defined. Aim: To characterize stool cytokine profiles and pro-/anti-inflammatory balance in children with ASD across development. Methods: We analyzed stool samples from 283 children (109 controls, 104 mild ASD, 70 severe ASD; age 0.9–21.5 years) recruited at a tertiary centre. Nine cytokines (IFN-γ, IL-1α, IL-1β, IL-4, IL-6, IL-8, IL-10, IL-17, TNF-α) were measured using a Luminex multi-plex assay; IL-15 was excluded due to >70% missing values. Group comparisons used Mann–Whitney U tests, with age stratification at the cohort median (≤9.5 vs. >9.5 years). A composite pro-/anti-inflammatory ratio (IL-1α + IL-1β + IL-6 + IL-8 + IL-17 + TNF-α + IFN-γ divided by IL-4 + IL-10) was calculated. Results: In the overall cohort, stool IL-8 and IL-4 were significantly decreased in ASD versus controls (IL-8: median 0.36 vs. 0.49 ng/L, p = 0.0041; IL-4: 0.28 vs. 0.30 ng/L, p = 0.0316), with a graded reduction from controls to mild and severe ASD. Age-stratified analysis revealed that IL-8 reduction was confined to younger children (≤9.5 years; p = 0.0025) and absent in older children, while IL-1β was significantly reduced in younger ASD children and tended to reverse in older ASD children. The pro-/anti-inflammatory ratio was markedly elevated in severe ASD (median 491 vs. 209 in controls; p = 0.059), particularly in older children. Stool IL-8 and IL-1β correlated inversely with CARS scores within the ASD group. Conclusions: Children with ASD show decreased stool IL-8 and IL-4 and a shift toward a pro-inflammatory cytokine balance, with the strongest alterations during early childhood. These findings are consistent with the hypothesis of a developmental window of intestinal immune dysregulation in ASD, with stool IL-8 as the primary FDR-corrected finding. The present cross-sectional data do not establish causality and independent replication is required before clinical conclusions are drawn.

Autism spectrum disorder (ASD) has been associated with alterations in the gut microbiota and its metabolites, particularly short-chain fatty acids (SCFAs) and microbiota-derived tryptophan catabolites, which may influence neurodevelopment through immune and epigenetic mechanisms. We investigated whether stool SCFAs and tryptophan-pathway metabolites differ between children with ASD and typically developing controls, and whether these metabolites associate with ASD severity and systemic biochemical signatures. In this cross-sectional study, we analyzed stool samples from 229 children (160 with ASD, 69 controls) with complete SCFA and tryptophan-metabolite data, while urine metabolomics data were available for a subset and were used for exploratory stool–urine integration analyses. Children with ASD and controls were similar in age, but the ASD group had a higher proportion of males. Absolute concentrations of individual SCFAs, total SCFAs, and derived indices were broadly comparable between groups; nominal differences in propionate/acetate ratio and caproate did not remain significant after false discovery rate correction. Similarly, stool tryptophan-pathway metabolites reported as ng/a.u. based on the NanoDrop-derived proxy (tryptophan, kynurenine, indole-3-acetic, indole-3-lactic, indole-3-propionic, indole-3-aldehyde, N-acetyl-tryptophan, serotonin, melatonin, tryptamine) and functional ratios (kynurenine/tryptophan, indole-derived/tryptophan, serotonin/tryptophan) showed no robust ASD–control differences; N-acetyl-tryptophan was nominally higher in ASD but did not survive multiple-testing correction. In the ASD subgroup with available Childhood Autism Rating Scale (CARS) data (n = 34), SCFA and tryptophan indices showed only weak, non-significant correlations with global ASD severity. In contrast, correlation analyses revealed two coherent metabolic modules, i.e., an SCFA block with very strong internal correlations among individual SCFAs and total SCFAs and a tryptophan block with strong correlations between metabolites and their normalized ratios, while cross-module correlations were modest. These results indicate that stool SCFA and microbiota-derived tryptophan profiles do not robustly distinguish ASD from controls in this cohort, but they form stable metabolic modules compatible with microbiome–epigenome frameworks.

Background: Autism spectrum disorder (ASD) is biologically heterogeneous, and metabolomics may help characterise biochemical variability. Capillary dried blood spot (DBS) sampling is attractive for paediatric research, but age-stratified, class-resolved DBS studies spanning childhood and adolescence are scarce.Methods: We analysed capillary DBS samples from two cross-sectional cohorts: 63 children with ASD and 29 neurotypical controls aged 5–12 years, and 30 adolescents with ASD and 14 controls aged 12–18 years. Metabolites across five biochemical classes were quantified by a gas chromatography–Orbitrap (GC–Orbitrap) mass-spectrometry workflow. ASD–control differences were assessed within each cohort by Mann–Whitney tests, Spearman correlations, Benjamini–Hochberg false-discovery-rate (FDR) correction, and covariate-adjusted linear models. Secondary analyses were pre-specified and exploratory.Findings: No metabolite reached FDR-corrected significance in either cohort (smallest FDR 0·717 in children, 1·000 in adolescents). Among uncorrected associations, succinic acid (adjusted p=0·007) and cholesterol (adjusted p=0·018) were nominally higher in children with ASD. No adolescent metabolite was significant at any stage–none reached unadjusted nominal significance (smallest p=0·054) and none survived FDR correction; covariate-adjusted models are reported only as descriptive output. A formal cross-cohort test found no direction change surviving correction (one of 66 nominal). Nominal effects were stronger in males. No metabolite was associated with autism severity (CARS) at p<0·05 in either cohort.Interpretation: Capillary DBS GC–Orbitrap metabolomics detected only nominal, age-patterned ASD-associated differences, none surviving multiplicity correction. The data do not establish biomarkers but demonstrate the feasibility of openly-deposited paediatric DBS metabolomics and generate hypotheses for adequately powered, longitudinal studies.