Integrated Multiomics Reveals Gut–Brain Axis Dysregulation and Phenotype-Specific Metabolic Signatures in Children with Febrile Seizures

Background: Febrile seizures (FSs) are the most common neurological emergency in early childhood; however, the biological basis of disease heterogeneity remains poorly understood. Although growing evidence suggests that gut–brain axis dysregulation contributes to seizure susceptibility, it remains unclear whether gut microbiota-associated metabolic disturbances are linked to clinical phenotypes, particularly simple FS (SFS) and complex FS (CFS). Methods: An integrated multiomics study was conducted in clinically characterized pediatric cohorts, comprising 50 children with FS and 50 healthy controls, and their gut microbiota was profiled via 16S rRNA sequencing. As some pediatric serum specimens did not meet the minimum volume requirement of the analytical platform, serum amino acid profiling was performed in a subset of samples using an equal-volume pooling strategy. In brief, two individual serum samples from the same study group were combined into one composite sample, yielding 25 pooled samples in the FS group and 25 in the control group. Subsequently, untargeted fecal metabolomics was performed in an expanded cohort of 53 healthy controls, 50 children with SFS, and 42 children with CFS. Additionally, the central metabolic profiles of the CFS and SFS groups were compared using untargeted cerebrospinal fluid metabolomics. Given the variation in sample sizes across omics platforms, each dataset was analyzed within its corresponding eligible subset, and cross-omics integration was interpreted primarily at the pathway and phenotype levels. Results: Children with FS exhibited reduced gut microbial diversity and altered microbial composition, characterized by the enrichment of Streptococcus, Enterococcus, and Escherichia–Shigella, along with the depletion of beneficial taxa, including Faecalibacterium, Lachnoclostridium, and Parasutterella. Functional prediction indicated significant changes in amino acid-related pathways, especially arginine and proline metabolism, amino acid metabolism, and glutathione metabolism. Serum profiling showed elevated levels of phenylalanine, kynurenine, and γ-aminobutyric acid, along with reduced levels of tryptophan, threonine, lysine, glutamine, taurine, citrulline, 3-methylhistidine, α-aminobutyric acid, hydroxyproline, and phosphoethanolamine. Correlation analysis identified Lachnoclostridium and Parasutterella as key taxa associated with neuroactive metabolites. Additionally, fecal metabolomics revealed that both SFS and CFS samples exhibited significant metabolic divergence from the controls, with arginine biosynthesis emerging as a shared altered pathway and L-arginine reduced in both phenotypes. Notably, cerebrospinal fluid metabolomics demonstrated clear metabolic separation between CFS and SFS, signifying phenotype-specific central metabolic signatures. Conclusions: FS is related to gut microbiota dysbiosis, systemic amino acid remodeling, and phenotype-associated metabolic stratification. Arginine metabolism may represent a shared mechanistic hub across FS phenotypes, while central metabolic divergence may contribute to the biological distinction between SFS and CFS. These findings establish a multiomics framework for understanding FS pathogenesis and identifying potential biomarkers and therapeutic targets.