Related Experiment Video
Updated: Jul 18, 2026

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
Published on: August 21, 2019
Characterizing immune and metabolic profiles in autism spectrum disorder through combined
Yuxuan Meng1, Jinrui Jia2, Yanheng Ding1
1College of Life Sciences, Northwest A&F University, Yangling, 712100, China.
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.
More Related Videos
03:39Author Spotlight: Multi-Layered Approach to Understand Postnatal Functions of Pancreatic Islets in Non-Human Primates
Published on: November 8, 2024
09:52A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease
Published on: January 10, 2025