Genes with High Network Connectivity Are Enriched for Disease Heritability

Area of Science:

• Genetics
• Computational Biology
• Disease Biology

Background:

• Gene networks play a crucial role in understanding disease mechanisms.
• Previous studies suggest the involvement of biological pathways and networks in complex traits.

Purpose of the Study:

• To formally assess the role of gene networks and pathways in disease biology.
• To identify enriched annotations for 42 diseases and complex traits using stratified LD score regression.

Main Methods:

• Constructed pathway, network, and pathway+network annotations.
• Applied stratified LD score regression to 42 diseases and complex traits (average N = 323K).
• Analyzed 18,119 biological pathways and four published gene networks.

Main Results:

• Identified 156 statistically significant pathway-trait pairs (FDR < 5%) after stringent conditioning.
• Network connectivity annotations were significantly enriched, but largely explained by overlap with regulatory annotations.
• Pathway+network annotations were also significantly enriched, with enrichments largely explained by the baseline-LD model.

Conclusions:

• Gene network connectivity is informative for disease architectures.
• Regulatory annotations are crucial and may subsume information from gene networks.
• Accounting for known annotations is essential in gene network analyses.