Integration of biological networks and pathways with genetic association studies.
Millions of genetic variants have been assessed for their effects on the trait of interest in genome-wide association studies (GWAS). The complex traits are affected by a set of inter-related genes. However, the typical GWAS only examine the association of a single genetic variant at a time. The individual effects of a complex trait are usually small, and the simple sum of these individual effects may not reflect the holistic effect of the genetic system. High-throughput methods enable genomic studies to produce a large amount of data to expand the knowledge base of the biological systems. Biological networks and pathways are built to represent the functional or physical connectivity among genes. Integrated with GWAS data, the network- and pathway-based methods complement the approach of single genetic variant analysis, and may improve the power to identify trait-associated genes. Taking advantage of the biological knowledge, these approaches are valuable to interpret the functional role of the genetic variants, and to further understand the molecular mechanism influencing the traits. The network- and pathway-based methods have demonstrated their utilities, and will be increasingly important to address a number of challenges facing the mainstream GWAS.
Department of Epidemiology, Emory University, Rollins School of Public Health, Atlanta, GA 30322, USA. yvsun@emory.edu
Yan V
YV
Sun
D019295:Computational Biology / Q000379:methods; D053263:Gene Regulatory Networks; D056726:Genetic Association Studies; D055106:Genome-Wide Association Study; D006801:Humans; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D015398:Signal Transduction; D014584:User-Computer Interface