Selection of SNP subsets for association studies in candidate genes: comparison of the power of different strategies to detect single disease susceptibility locus effects

Emmanuelle Cousin,Jean-Francois Deleuze,Emmanuelle Genin

doi:10.1186/1471-2156-7-20

Emmanuelle Cousin, Jean-Francois Deleuze + Show 1 more

Open Access

https://doi.org/10.1186/1471-2156-7-20

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Journal: BMC genetics	Publication Date: Apr 5, 2006
Citations: 27	License type: cc-by

Affiliation: Sanofi (France), Hôpital Paul-Brousse

Abstract

BackgroundThe recent advances in genotyping and molecular techniques have greatly increased the knowledge of the human genome structure. Millions of polymorphisms are reported and freely available in public databases. As a result, there is now a need to identify among all these data, the relevant markers for genetic association studies. Recently, several methods have been published to select subsets of markers, usually Single Nucleotide Polymorphisms (SNPs), that best represent genetic polymorphisms in the studied candidate gene or region.ResultsIn this paper, we compared four of these selection methods, two based on haplotype information and two based on pairwise linkage disequilibrium (LD). The methods were applied to the genotype data on twenty genes with different patterns of LD and different numbers of SNPs. A measure of the efficiency of the different methods to select SNPs was obtained by comparing, for each gene and under several single disease susceptibility models, the power to detect an association that will be achieved with the selected SNP subsets.ConclusionNone of the four selection methods stands out systematically from the others. Methods based on pairwise LD information turn out to be the most interesting methods in a context of association study in candidate gene. In a context where the number of SNPs to be tested in a given region needs to be more limited, as in large-scale studies or wide genome scans, one of the two methods based on haplotype information, would be more suitable.

Highlights

The recent advances in genotyping and molecular techniques have greatly increased the knowledge of the human genome structure
In a context where the number of Single Nucleotide Polymorphisms (SNPs) to be tested in a given region needs to be more limited, as in large-scale studies or wide genome scans, one of the two methods based on haplotype information, would be more suitable
The four selection methods were applied to the genotype data on twenty candidate genes with various numbers of

Summary

Introduction

The recent advances in genotyping and molecular techniques have greatly increased the knowledge of the human genome structure. There is a need to identify among all these data, the relevant markers for genetic association studies. Several methods have been published to select subsets of markers, usually Single Nucleotide Polymorphisms (SNPs), that best represent genetic polymorphisms in the studied candidate gene or region. The high density of Single-Nucleotide Polymorphisms (SNPs) throughout the genome and the easiness of their genotyping have made these markers a widely used tool for association studies in candidate genes. During the last few years, new developments in genetics have enhanced even more their privileged situation. Hundreds of thousands of SNPs are reported in public or private databases [2,3,4] and the number of markers described within a candidate gene often reaches several tens. C3AR1 – SNPs CCR2 – SNPs CEBPB – 10 SNPs CSF2 – 17 SNPs FCN3 – 14 SNPs FGL2 – 6 SNPs IFNG – 13 SNPs IL13 – 16 SNPs IL24 – 24 SNPs IL9 – 14 SNPs LTA – 19 SNPs LTB – 7 SNPs MC1R – SNPs PLAU – SNPs PROCR – 13 SNPs RELA – 12 SNPs SERPINC1 – 27 SNPs

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Discussion

Conclusion