Repositioning drugs for autism spectrum disorder: An integrated network analysis of blood and brain tissue key driver genes.

Researchers used computer analysis to study genes in blood and brain samples to find new drug treatments for autism. They found specific genes that might be important in autism and identified 23 existing drugs that could potentially help. Two drugs, sulpiride and everolimus, showed particular promise. The study also found 12 new genes linked to autism that affect brain and immune system function.

This computational study used network analysis to identify potential drug treatments for autism spectrum disorder by analyzing gene expression data from blood and brain tissue samples. Researchers identified 204 key driver genes in blood samples related to cell cycle regulation and stress response, and 290 key driver genes in brain samples focused on ribosomal activity and protein production. Through integrated protein-protein interaction network analysis, they discovered 16 shared key driver genes involved in RNA metabolism, protein regulation, and signaling pathways. Drug repositioning analysis revealed 23 potential therapeutic drugs, with sulpiride and everolimus showing particular promise.

Nineteen drugs demonstrated neurological significance, including six with substantial blood-brain barrier permeability.

Findings are preliminary and require experimental validation before clinical application. The identified drugs need safety and efficacy testing specifically for autism. The molecular signatures could guide future research into autism mechanisms and biomarker development.

This is a computational study using existing gene expression data without experimental validation. No sample sizes reported for the datasets analyzed. Drug repositioning predictions require clinical validation. The study does not provide evidence of actual therapeutic efficacy in humans.

Autism spectrum disorder (ASD) is a complex neurological condition marked by social, communication, and behavioral challenges. Current treatments are limited, with few approved drugs. This study used network analysis of key driver genes from blood and brain tissues to identify potential therapeutic drugs for ASD. We examined Gene Expression Omnibus (GEO) data from postmortem brain (GSE28521) and blood leukocyte (GSE42133) samples to find differentially expressed genes.

Key driver genes were identified using weighted key driver analysis, supported by literature, knockout mouse model databases, and enrichment analysis. Drug repositioning was performed with PharmOmics and Connectivity Map (CMap) platforms. In blood samples, 204 key driver genes were discovered, associated with cell cycle regulation and stress response. In brain samples, 290 key driver genes focused on ribosomal activity and protein production.

An integrated protein-protein interaction (PPI) network identified 16 shared key driver genes, demonstrating common disease signatures including RNA metabolism, protein regulation, SLIT and ROBO signaling, and antiviral pathways. Drug repositioning revealed 23 potential drugs for ASD, with sulpiride and everolimus demonstrating promise, and 19 drugs exhibiting neurological significance, including six with substantial blood-brain barrier permeability. Our study reveals both tissue-specific and shared molecular signatures of ASD in blood and brain tissues through PPI network analysis. We identified 16 key driver genes and 23 potential therapeutic drugs.

Additionally, we discovered twelve novel key driver genes associated with ASD, emphasizing their roles in neurological and immune functions. These findings enhance our understanding of the molecular basis of ASD and suggest new therapeutic possibilities.