Using single nucleotide polymorphisms to investigate association between a candidate gene and disease

The role of linkage disequilibrium in case-only studies of gene-environment interactions

Gene-environment (G × E) interactions have been invoked to account, at least in part, for the gap between the known heritability of common human diseases and the phenotypic variation hitherto explained by genetic variants. Noteworthy in this context, a case-only (CO) design has been proposed in the past as a means to detect G × E interactions possibly more efficiently than by using classical case-control and cohort designs. So far, however, most CO studies have followed a candidate (or single) gene approach, and the genome-wide utility of the CO design is still more or less unknown. In particular, the way in which linkage disequilibrium (LD) impacts upon the chance to detect G × E interaction through the analysis of proxy markers has not been studied in much detail before. Therefore, we systematically assessed the power to indirectly detect a given G × E interaction through exploiting LD in a CO design. Our simulations revealed a strong relationship between LD and detection power that was subsequently validated in a real colorectal cancer data set.

Schistosomal hepatic fibrosis and the interferon gamma receptor: a linkage analysis using single-nucleotide polymorphic markers

A minority of individuals infected with the parasite Schistosoma mansoni develops hepatic fibrosis. HLA studies in Egypt and a candidate gene search in a Sudanese population indicate that the host's genetics contribute to disease susceptibility. In an Egyptian community, 32.7% of individuals 11 years and older had significant fibrosis by WHO ultrasound criteria. Linkage to 10 candidate genes was tested using 89 affected sibling pairs from 40 pedigrees in this community. The candidates included genes that initiate fibrosis, participate in collagen synthesis, or control collagen degradation. Two to four single-nucleotide polymorphisms (SNPs) were genotyped per locus, and 188 individuals were genotyped at 48 markers. Model-free modified Haseman-Elston analysis identified linkage to a SNP in the interferon gamma receptor locus (P=0.000001). There was also weak evidence for linkage to the interleukin 13-4 region and tissue growth factor beta 1.

Haplotype sharing analysis with SNPs in candidate genes: the Genetic Analysis Workshop 12 example

Haplotype sharing analysis was used to investigate the association of affection status with single nucleotide polymorphism (SNP) haplotypes within candidate gene 1 in one sample each from the isolated and the general population of Genetic Analysis Workshop (GAW) 12 simulated data. Gene 1 has direct influence on affection and harbors more than 70 SNPs. Haplotype sharing analysis depends heavily on previous haplotype estimation. Using GENEHUNTER haplotypes, strong evidence was found for most SNPs in the isolated population sample, thus providing evidence for an involvement of this gene, but the maximum -log(10)(p) values for the haplotype sharing statistics (HSS) test statistic did not correspond to the location of the true variant in either population. In comparison, transmission disequilibrium test (TDT) analysis showed the strongest results at the disease-causing variant in both populations, and these were outstanding in the general population. In this example, TDT analysis appears to perform better than HSS in identifying the disease-causing variant, using SNPs within a candidate gene in an outbred population. Simulations showed that the performance of HSS is hampered by closely spaced SNPs in strong linkage disequilibrium with the functional variant and by ambiguous haplotypes.