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| This article is part of the supplement: The Third International Symposium on the Molecular Biology of Breast CancerPoster PresentationChromosome-wide pharmacogenetics: localisation and linkage disequilibrium of genes coding for ROS metabolism and signalling1Department of Genetics, The Norwegian Radium Hospital, Oslo, Norway 2Section of Medical Statistics, University of Oslo, Norway 3Department of Medical Sciences, Uppsala University, Uppsala, Sweden Molde, Norway. 22–26 June 2005 Breast Cancer Research 2005, 7(Suppl 2):P1.15doi:10.1186/bcr1102
BackgroundPharmacogenetic studies provide data of increasingly many SNPs in relation to response to various treatments of psychological disorders, cardiovascular disease and cancer. Simultaneously, the HapMap and projects like it reveal the linkage disequilibrium (LD) map of unselected genes in different human populations. To what extent does this knowledge of the LD domains affect previous findings from pharmacogenetic studies of single candidate SNPs? Here we select candidate genes as part of a given functional pathway, and report their chromosomal localization and extent of LD. MethodsA total of 193 breast cancer patients have been genotyped for 725 SNPs in 206 genes selected through the candidate gene approach. Two hundred and fifty-three of the SNPs have also been genotyped in a cohort of 109 healthy Norwegian women. SNPs that had a discovery rate lower than 75% were excluded. Hardy-Weinberg equilibrium was calculated prior to further statistical analysis of LD. LD estimations were made using PHASE, a program that implements methods for calculating haplotypes from population genotype data [1]. ResultsThe 725 SNPs were divided between 206 different genes with 1–20 SNPs per gene distributed on all chromosomes. Initially, SNPs were grouped in clusters containing a minimum of three SNPs with no more than 100 kb between neighbouring SNPs. Based on the PHASE output, D' and the P value of the Fisher's exact test were calculated. We observed strong LD in 74 genes, and 10 genes were split into more than one LD domain. Furthermore, neighbouring clusters of genes were studied for common LD. Genotype frequencies and the extent of LD were compared in a case–control study when possible. ConclusionOur findings are restricted by our choice of genes and the number of SNPs per gene. Nevertheless, they reveal LD between SNPs in multiple genes, which have been previously studied in separate and independent studies. This notion of the existing LD may be of potential value in designing new pharmacogenetic studies. References
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