1. ¹Medical Genomics Section, Department of Clinical Genetics, Vrije University Medical Center, Amsterdam, The Netherlands
2. ²Department of Biological Psychology, VU University, Amsterdam, The Netherlands
3. ³Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
4. ⁴Department of Psychiatry, EMGO Institute, Institute of Neuroscience, Vrije University Medical Center, Amsterdam, The Netherlands
5. ⁵Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
6. ⁶Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands

Correspondence: Dr P Heutink, Human Genetics, section Medical Genomics, VU Medical Center, Van der Boechorsstraat 7, 1081 BT Amsterdam, Amsterdam, The Netherlands. Tel: +31 205989962; Fax: +31 2059983596; E-mail: p.heutink@vumc.nl

Received 27 August 2008; Revised 18 October 2008; Accepted 20 November 2008; Published online 7 January 2009.

Abstract

The HapMap project has facilitated the selection of tagging single nucleotide polymorphisms (tagSNPs) for genome-wide association studies (GWAS) under the assumption that linkage disequilibrium (LD) in the HapMap populations is similar to the populations under investigation. Earlier reports support this assumption, although in most of these studies only a few loci were evaluated. We compared pair-wise LD and LD block structure across autosomes between the Dutch population and the CEU–HapMap reference panel. The impact of sampling distribution on the estimation of LD blocks was studied by bootstrapping. A high Pearson correlation (genome-wide; 0.93) between pair-wise r² for the Dutch and the CEU populations was found, indicating that tagSNPs from the CEU–HapMap panel capture common variation in the Dutch population. However, some genomic regions exhibited, significantly lower correlation than the genome-wide estimate. This might decrease the validity of HapMap tagSNPs in these regions and the power of GWAS. The LD block structure differed considerably between the Dutch and CEU–HapMap populations. This was not explained by demographic differences between the CEU and Dutch samples, as testing for population stratification was not significant. We also found that sampling variation had a large effect on the estimation of LD blocks, as shown by the bootstrapping analysis. Thus, in small samples, most of the observed differences in LD blocks between populations are most likely the result of sampling variation. This poor concordance in LD block structure suggests that large samples are required for robust estimations of local LD block structure in populations.