Integrated multifactor analysis explores core dysfunctional modules in autism spectrum disorder.

Area of Science:

• Neuroscience
• Genetics
• Bioinformatics

Background:

• Autism spectrum disorder (ASD) is a significant early childhood neurodevelopmental disease with poorly understood molecular underpinnings.
• Identifying the molecular mechanisms of ASD is crucial for understanding its role as a major cause of childhood disability.

Purpose of the Study:

• To perform integrated multifactor analysis of RNA-Seq data to explore dysfunctional molecular modules in ASD.
• To identify pivot regulators, including transcription factors (TFs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs), involved in ASD pathogenesis.

Main Methods:

• Utilized RNA-Seq data from corpus callosum of ASD patients and normal individuals.
• Applied protein-protein interaction (PPI) networks and Weighted Gene Co-expression Network Analysis (WGCNA) to identify differentially expressed genes (DEGs) and co-expression modules.
• Integrated transcription factor (TF)-target and RNA-associated interactions to identify pivot regulators.

Main Results:

• Identified 25 co-expression modules with DEGs significantly involved in nervous system, sensory system, phylogenetic system, and signaling pathways.
• Discovered 67 pivot TFs, 13 pivot miRNAs, and 6 pivot lncRNAs as key regulators.
• Pivot miRNAs were enriched in neural and mental-associated biological processes, while pivot TFs were linked to transcriptional regulation, immune system, and organ development.

Conclusions:

• Deciphered a multifactor dysfunctional co-expression subnetwork implicated in ASD.
• Uncovered core dysfunctional modules contributing to ASD.
• Enhanced the understanding of the molecular mechanisms underlying autism spectrum disorder.