AI Insight
Researchers used systems biology and machine learning to analyze gene expression data from autism spectrum disorder patients, identifying TLR8 and CASP4 as candidate biomarker genes. These genes were validated in a rat autism model, showing increased expression in the hippocampus, with TLR8 also elevated in peripheral blood. The study also identified specific microRNAs (miR-891b, miR-627-3p, and miR-26b-5p) as potential regulators of these genes.
Why it matters
These findings could provide new biomarkers for ASD diagnosis and potential therapeutic targets for treatment development. The identification of accessible peripheral blood markers (TLR8) is particularly valuable for non-invasive clinical applications.
Understand the Science
by Sara Hosseinpoor, Hakimeh Zali, Hassan Zohrevand, Seyed Amir Mirmotalebisohi, Fariba Khodagholi, Maryam Bazrgar, Sareh Asadi, Abolhassan Ahmadiani
Background
Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders whose underlying molecular mechanisms and biological processes remain incompletely understood. In this study, we used a multi-layered systems biology approach to prioritize candidate genes and regulatory factors associated with ASD.
Method
Gene expression data from peripheral blood samples were obtained from the Gene Expression Omnibus (GEO) database (GSE18123). Using analyses performed in R software, differentially expressed genes (DEGs) in patients with ASD were identified (p-value < 0.05 and |log2FC| > 0.5). These DEGs were used to perform weighted gene co-expression network analysis (WGCNA) and construct a protein–protein interaction (PPI) network. By integrating the results of these network analyses with feature selection techniques (LASSO and random forest feature importance), candidate genes associated with ASD were prioritized and evaluated using qRT-PCR in the valproic acid (VPA)-induced rat model of autism. Furthermore, a gene regulatory network (GRN) was constructed to identify the regulatory factors associated with DEGs.
Result
TLR8 and CASP4 were prioritized as candidate genes that may be associated with ASD, because they were located within the co-expression module that showed the strongest correlation with ASD, were identified as key nodes of the PPI network, and were selected by feature selection algorithms. Our experimental validation showed increased expression of TLR8 and CASP4 in the autism model compared with controls; TLR8 was upregulated in both the hippocampus and peripheral blood, whereas CASP4 was upregulated only in the hippocampus. Furthermore, GRN analysis identified miR-891b and miR-627-3p as potential regulators of TLR8, and miR-26b-5p as associated with CASP4.
Conclusion
These findings indicate that CASP4 and TLR8, together with their associated regulatory miRNAs, may represent promising biomarkers and potential therapeutic targets for future ASD research and contribute to a better understanding of the pathophysiological mechanisms underlying ASD.