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Network Diffusion-Based Prioritization of Autism Risk Genes Identifies Significantly Connected Gene Modules
Ettore Mosca1, Matteo Bersanelli2, Matteo Gnocchi1
1Bioinformatics Group, Institute of Biomedical Technologies, National Research Council of Italy, Segrate, Italy.
Frontiers in Genetics
|October 11, 2017
Summary
This study identifies autism spectrum disorder (ASD) disease modules using network analysis of genetic data. Findings reveal key genes in neuronal function, comorbidities, and cellular processes linked to ASD.
Area of Science:
- Genetics
- Computational Biology
- Neuroscience
Background:
- Autism spectrum disorder (ASD) exhibits significant genetic heterogeneity, evidenced by limited overlap in risk gene lists across studies.
- Molecular networks offer a framework to integrate findings from multiple genome-wide studies for ASD.
Purpose of the Study:
- To identify ASD-associated genetic "disease modules" by analyzing multiple ASD risk gene lists.
- To leverage network analysis to uncover genes and pathways implicated in ASD.
Main Methods:
- Employed a network diffusion-based approach to jointly analyze multiple ASD risk gene lists.
- Performed genome-scale gene prioritization and identified significantly connected gene modules related to ASD.
Main Results:
- Identified gene modules significantly associated with ASD.
- Predicted novel genes functionally related to known ASD risk genes.
- Associated identified genes with synaptic and neuronal functions, comorbid syndromes, epigenetics, cell cycle, cell adhesion, and cancer.
Conclusions:
- Network analysis effectively integrates heterogeneous genetic data to identify ASD disease modules.
- The identified modules highlight the involvement of synaptic and neuronal pathways, comorbidities, and other cellular processes in ASD pathogenesis.
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