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A network approach to prioritizing susceptibility genes for genome-wide association studies
Somayeh Kafaie1, Yuanzhu Chen1, Ting Hu1
1Department of Computer Science, Memorial University, St. John's, NL, Canada.
Genetic Epidemiology
|March 13, 2019
Summary
This study identifies key genes influencing colorectal cancer (CRC) risk by analyzing gene interactions using network science. It highlights COL22A1, RGS7, WWOX, and CELF2 as significant susceptibility genes for CRC.
Area of Science:
- Genetics
- Bioinformatics
- Network Science
Background:
- Complex diseases like cancer result from multiple interacting genetic alterations.
- Gene-gene interactions (epistasis) pose challenges for traditional univariable analysis in genome-wide association studies.
- Network science offers advanced methods for modeling epistasis and understanding gene-phenotype relationships.
Purpose of the Study:
- To construct a statistical epistasis network for colorectal cancer (CRC).
- To employ network measures for prioritizing genes involved in CRC risk via synergistic interactions.
- To identify potential biological targets for CRC through network analysis.
Main Methods:
- Construction of a statistical epistasis network specific to colorectal cancer.
- Computation and analysis of global and local network properties.
- Utilizing topological features like edge strength, vertex centrality, and graphlet occurrences to rank genetic variations.
Main Results:
- Identification of 512 top-ranked single-nucleotide polymorphisms (SNPs) associated with CRC risk.
- Prioritization of four key susceptibility genes: COL22A1, RGS7, WWOX, and CELF2.
- These genes were consistently identified as most influential across multiple network metrics.
Conclusions:
- Network science provides effective tools for dissecting complex gene interactions in diseases like CRC.
- The identified susceptibility genes (COL22A1, RGS7, WWOX, CELF2) represent promising targets for further CRC research and potential therapeutic strategies.
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