Abstract
Recent genome-wide association studies on several complex diseases have focused on individual single-nucleotide polymorphism (SNP) analysis; however, not many studies have reported interactions among genes perhaps because the gene-gene and gene-environment interaction analysis could be infeasible due to heavy computing requirements. In this study we propose a new strategy for exploring the interactions among haplotypes. The proposed method consists of two steps. Step 1 tests the single-SNP association of whole genome with multiple testing corrections and finds the haplotype blocks of the significant SNPs. Step 2 performs interaction analysis of haplotypes within blocks. Our proposed method is applied to the rheumatoid arthritis data for Genetic Analysis Workshop 16.
Highlights
Complex diseases such as rheumatoid arthritis (RA) are the results of a complex interplay of genetic and environmental factors
We propose genome-wide analysis of haplotype interaction (GWAHI) to discover interactions between unlinked regions based on haplotypes
Single-single-nucleotide polymorphism (SNP) and haplotype association analysis SNP and haplotype association analysis identified 411 significant SNPs and 146 haplotype blocks, among which 255 SNPs and 133 haplotypes were from chromosome 6
Summary
Complex diseases such as rheumatoid arthritis (RA) are the results of a complex interplay of genetic and environmental factors. A linkage study of Jawaheer et al [1] showed that regions from chromosome 1 interact with chromosome 6, resulting in synergistic effect on risk of RA. Simulation studies showed that interaction analysis can be more powerful to detect disease associated genes than analysis ignoring interactions even after correction for multiple testing [2,3]. Because a haplotype comprises multiple SNPs on the same inherited chromosomes, the haplotype-based approaches can provide insight into factors influencing the dependency among genetic markers. Such insight may provide information essential for understanding human evolution and for identifying cisinteractions between two or more causal variants [6]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
