Genome-wide association study of acute post-surgical pain in humans

Abstract

Aims: Testing a relatively small genomic region with a few hundred SNPs provides limited information. Genome-wide association studies (GWAS) provide an opportunity to overcome the limitation of candidate gene association studies. Here, we report the results of a GWAS for the responses to an NSAID analgesic.

Materials & methods: European Americans (60 females and 52 males) undergoing oral surgery were genotyped with Affymetrix 500K SNP assay. Additional SNP genotyping was performed from the gene in linkage disequilibrium with the candidate SNP revealed by the GWAS.

Results: GWAS revealed a candidate SNP (rs2562456) associated with analgesic onset, which is in linkage disequilibrium with a gene encoding a zinc finger protein. Additional SNP genotyping of ZNF429 confirmed the association with analgesic onset in humans (p = 1.8 x 10(-10), degrees of freedom = 103, F = 28.3). We also found candidate loci for the maximum post-operative pain rating (rs17122021, p = 6.9 x 10(-7)) and post-operative pain onset time (rs6693882, p = 2.1 x 10(-6)), however, correcting for multiple comparisons did not sustain these genetic associations.

Conclusion: GWAS for acute clinical pain followed by additional SNP genotyping of a neighboring gene suggests that genetic variations in or near the loci encoding DNA binding proteins play a role in the individual variations in responses to analgesic drugs.

Figures

Figure 1. Multilayer genetic association study

(A) Plot of statistical significance (−log10P) values of genotyped SNPs across the whole genome for analgesic onset time after ketorolac administration. Reference line indicates threshold for genome wide significance (p = 4.2 × 10−7). Horizontal axis represent reference SNPs for the chromosomal location. (B) A single haploblock from HapMap containing significant associated SNPs and ZNF429. (C) Associations between four ZNF429 SNPs and analgesic onset (p = 1.8 × 10−10, degrees of freedom = 103, F = 28.3, mean ± standard error).