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. 2014 Feb;15(2):169-80.
doi: 10.1016/j.jpain.2013.09.015. Epub 2013 Oct 12.

Associations between cytokine gene variations and severe persistent breast pain in women following breast cancer surgery

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Associations between cytokine gene variations and severe persistent breast pain in women following breast cancer surgery

Kimberly Stephens et al. J Pain. 2014 Feb.

Abstract

Persistent pain following breast cancer surgery is a significant clinical problem. Although immune mechanisms may play a role in the development and maintenance of persistent pain, few studies have evaluated for associations between persistent breast pain following breast cancer surgery and variations in cytokine genes. In this study, associations between previously identified extreme persistent breast pain phenotypes (ie, no pain vs severe pain) and single nucleotide polymorphisms (SNPs) spanning 15 cytokine genes were evaluated. In unadjusted analyses, the frequency of 13 SNPs and 3 haplotypes in 7 genes differed significantly between the no pain and severe pain classes. After adjustment for preoperative breast pain and the severity of average postoperative pain, 1 SNP (ie, interleukin [IL] 1 receptor 2 rs11674595) and 1 haplotype (ie, IL10 haplotype A8) were associated with pain group membership. These findings suggest a role for cytokine gene polymorphisms in the development of persistent breast pain following breast cancer surgery.

Perspective: This study evaluated for associations between cytokine gene variations and the severity of persistent breast pain in women following breast cancer surgery. Variations in 2 cytokine genes were associated with severe breast pain. The results suggest that cytokines play a role in the development of persistent postsurgical pain.

Keywords: Cytokines; breast cancer surgery; candidate genes; persistent pain; polymorphism.

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Conflict of interest statement

Disclosures:

No conflicts of interest exist.

Figures

Figure 1
Figure 1
Differences in the percentages of patients in the no breast pain and severe breast pain latent classes who were homozygous for the common allele or heterozygous (TT+TC) or homozygous for the rare allele (CC) for rs11674595 in IL1R2.
Figure 2
Figure 2
IL10 linkage disequilibrium-based heatmap and haplotype analysis. In the figure embedded in the top row of the table, an ideogram of interleukin 10 (IL10) is presented above the white bar that represents the physical distance along human chromosome 1 (position 206,940,948 to 206,945,839; genome build 37.10, NG_012088.1). Exons are represented as boxes. Gray lines connecting the exons represent introns. The direction of transcription is from right to left. Reference sequence identifiers (rsID) for each single nucleotide polymorphism (SNP) are plotted both in terms of their physical distance (i.e., the white bar at the top of the figure) and also equidistantly in order to render the pairwise linkage disequilibrium (LD) estimates that were calculated and visualized with Haploview 4.2. The gene structure for IL10 (i.e., hg18 NM_000572) was rendered with FancyGene 1.4. The correlation statistics (r2 and D’) are provided in the heatmap. LD-based haplotype block definition was based on D’ confidence interval [11]. The haploblock is indicated in a bolded triangle and its component SNPs are rendered in bold font. Pairwise D’ values (range: 0–1, inclusive) were rendered in shades of grey, with dark grey diamonds representing D’ values approaching 1.0. When the r2 values (range of 0–100, inclusive) are not equal to 0 or 100, they are provided in a given diamond. The haplotypes observed in the haploblock are listed in each row, starting with the nucleotide composition across the seven SNPs that compose the haplotype (i.e., rs3024505, rs3024498, rs3024496, rs1878672, rs1518111, rs1518110, rs3024491) and the count frequency (%) of each haplotype observed in the no breast pain and severe breast pain classes. # The haplotype (i.e. CGCGATT) identified in the bivariate analyses (Table 1) remained significant after controlling for relevant confounders. n=number of individuals; s = number of alleles.

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