Comprehensive literature data-mining analysis reveals a broad genetic network functionally associated with autism...

Area of Science:

• Genetics
• Neuroscience
• Bioinformatics

Background:

• Genetic factors are widely recognized as the primary cause of Autism Spectrum Disorder (ASD).
• A comprehensive, systematically curated list of genes associated with ASD has been lacking.
• Previous research has not fully elucidated the functional interconnections among ASD-associated genes.

Purpose of the Study:

• To systematically identify and curate genes associated with Autism Spectrum Disorder (ASD) through extensive literature data mining.
• To analyze the functional enrichment and pathogenic significance of identified ASD genes using network analysis.
• To develop a prioritized ASD genetic database and associated metrics for future research.

Main Methods:

• Conducted a literature data mining analysis of over 2,064 articles (January 2000 - April 2016) to identify ASD-associated genes.
• Performed Gene Set Enrichment Analysis (GSEA), Sub-network Enrichment Analysis (SNEA), and Network Connectivity Analysis (NCA).
• Developed two literature metrics to prioritize curated ASD genes and created an ASD genetic database.

Main Results:

• Identified 488 target genes associated with Autism Spectrum Disorder (ASD).
• Found that 391 of the 488 genes were significantly enriched in 97 biological pathways (P<1x10‑8), indicating functional associations.
• Demonstrated that most identified ASD genes play roles in the pathogenesis of other neuropsychiatric disorders.

Conclusions:

• The genetic underpinnings of ASD involve a large, interconnected network of functionally associated genes.
• The developed ASD genetic database and prioritization metrics provide a valuable resource for future biological and genetic modeling.
• Understanding the network of ASD genes offers insights into shared genetic pathways with other neuropsychiatric conditions.