Characterizing immune and metabolic profiles in autism spectrum disorder through combined transcriptomics-metabonomics analysis

BACKGROUND: Autism Spectrum Disorders (ASD) encompass a range of complex neurodevelopmental conditions marked by difficulties in social communication, restricted interests, and repetitive behavior. In this study, we explore the potential interplay between metabolic and transcriptional alterations in ASD, aiming to uncover common biological disturbances that may contribute to the phenotype across cohorts. METHODS: Transcriptional and metabolomic data for ASD and typically developing (TD) samples were sourced from the GEO database. After rigorous quality control and alignment of transcriptomic data using DESeq2 identified differentially expressed genes (DEGs). For metabolomic data, MetaboAnalyst was used to find differentially expressed metabolites (DMs). Functional annotation was done using KEGG and GO, while Cytoscape facilitated network analysis. RESULTS: The analysis revealed significant upregulation of immune-related genes, including IL-1β and IFN-γ, indicating an activated immune response in ASD. Conversely, downregulation of synaptic genes suggests potential synaptic function impairments. These findings highlight the influence of immune responses on neurodevelopment. Furthermore, notable metabolic changes were observed, with increases in metabolites like phenylalanine and citrulline, alongside alterations in lipid metabolism, aligning with dysregulated immune pathways and synaptic signaling. Key transcription factors, such as RARA and NFKB2, were also identified, emphasizing their critical roles in modulating these interconnected biological processes. CONCLUSION: The parallel findings of dysregulation of metabolic and transcriptomic pathways in ASD from distinct cohorts point towards intricate commonalities that contribute to its phenotype. This multi-omics approach provides valuable insights and supports the development of precision medicine strategies. Future research should focus on longitudinal studies to explore these changes across developmental stages and environmental influences, offering a more comprehensive perspective on ASD management.