Identifying disease associations via genome-wide association studies
Background: Genome-wide association studies prove to be a powerful approach to identify the genetic basis of different human diseases. We studied the relationship between seven diseases characterized in a previous genome-wide association study by the Wellcorne Trust Case Control Consortium. Instead of doing a horizontal association of SNPs to diseases, we did a vertical analysis of disease associations by comparing the genetic similarities of diseases.Our analysis was carried out at four levels -the nucleotide level (SNPs), the gene level, the protein level (through protein-protein interaction network), and the phenotype level.Results: Our results show that Crohns disease, rheumatoid arthritis, and type 1 diabetes share evidence of genetic associations at all levels of analysis, offering strong molecular support for the current grouping of the diseases. On the other hand, coronary artery disease,hypertension, and type 2 diabetes, despite being considered as a natural group with potential aetiological overlap, do not show any evidence of shared genetic basis at all levels.Conclusions: Our study is a first attempt on mining of GWA data to examine genetic associations between different diseases. The positive result is apparently not a coincidence and hence demonstrates the promising use of our approach.
Wenhui Huang Pengyuan Wang Zhen Liu Liqing Zhang
Department of Computer Science, Virginia Tech,2050 Torgerson Hall, Blacksburg, VA 24061-0106, USA Department of Computer Science, Virginia Tech,2050 Torgerson Hall, Blacksburg, VA 24061-0106, USA Pr
国际会议
The 7th Asia-Pacific Bioinformatics Conference(第七届亚太生物信息学大会)
北京
英文
729-737
2009-01-01（万方平台首次上网日期，不代表论文的发表时间）