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We genotyped five single-nucleotide polymorphisms (SNPs) spaced evenly through ��2��3 using the 5�� exonuclease method ( Tegeder et?al., 2006). ��2��3 haplotypes were identified using the SAS/genetics software package (SAS Institute, Inc.), which implements a modified expectation-maximization ATP12A algorithm to reconstruct haplotypes from population genotype data. Linkage disequilibrium between SNPs was used to describe the nonindependence of alleles. The PCR reaction mixture consisted of 2.5 ml Master Mixture (Applied Biosystems), 100 nM detection probe for each allele, 900 nM forward and 900 nM reverse amplification primers, and 20 ng genomic DNA in a total reaction volume of 25 ��l. Amplification and detection were performed with an Smad inhibitor ABI Prism 7700 Sequence Detection System. Allele-specific signals were distinguished by measuring endpoint 6-FAM or VIC fluorescence intensities at 508 nm and 560 nm, respectively, and genotypes were generated using Sequence Detection System Software Version 1.7 (Applied Biosystems, CA). Genotyping error rate was directly determined by re-genotyping 25% of the samples, randomly chosen, for each locus. The overall error rate was?AZD3759 price summation of heat pain (i.e., wind-up). We used principal components analysis (PCA), as performed by the SAS statistical package (version 9.1, SAS Institute, Cary NC), as a data reduction exercise. From our raw pain scores, we derived a thermal wind-up score (Factor 3). We collected DNA from 169 Caucasian adults who participated in a prospective observational study of surgical discectomy for persistent lumbar root pain (Atlas et?al., 2001). The primary endpoint was persistent leg pain over the first postoperative year, using four ��leg pain�� variables normalized to Z-scores with mean 0 and standard deviation 1. The primary pain outcome variable for each individual was the mean of these four Z-scores. Genotype-phenotype associations for each SNP were sought by regression analysis. The covariates were a number of demographic, psychological and environmental factors, including sex, age, worker's compensation status, delay in surgery after enrollment and Short-Form 36 general health scale. Stepwise regression ( Zaykin et?al.