Multiple chronic pain states are associated with a common amino acid-changing allele in KCNS1

Abstract

Not all patients with nerve injury develop neuropathic pain. The extent of nerve damage and age at the time of injury are two of the few risk factors identified to date. In addition, preclinical studies show that neuropathic pain variance is heritable. To define such factors further, we performed a large-scale gene profiling experiment which plotted global expression changes in the rat dorsal root ganglion in three peripheral neuropathic pain models. This resulted in the discovery that the potassium channel alpha subunit KCNS1, involved in neuronal excitability, is constitutively expressed in sensory neurons and markedly downregulated following nerve injury. KCNS1 was then characterized by an unbiased network analysis as a putative pain gene, a result confirmed by single nucleotide polymorphism association studies in humans. A common amino acid changing allele, the 'valine risk allele', was significantly associated with higher pain scores in five of six independent patient cohorts assayed (total of 1359 subjects). Risk allele prevalence is high, with 18-22% of the population homozygous, and an additional 50% heterozygous. At lower levels of nerve damage (lumbar back pain with disc herniation) association with greater pain outcome in homozygote patients is P = 0.003, increasing to P = 0.0001 for higher levels of nerve injury (limb amputation). The combined P-value for pain association in all six cohorts tested is 1.14 E-08. The risk profile of this marker is additive: two copies confer the most, one intermediate and none the least risk. Relative degrees of enhanced risk vary between cohorts, but for patients with lumbar back pain, they range between 2- and 3-fold. Although work still remains to define the potential role of this protein in the pathogenic process, here we present the KCNS1 allele rs734784 as one of the first prognostic indicators of chronic pain risk. Screening for this allele could help define those individuals prone to a transition to persistent pain, and thus requiring therapeutic strategies or lifestyle changes that minimize nerve injury.

Figures

Figure 1

Global and functional DRG expression profiles in three neuropathic pain models. (A) Multidimensional scaling plot of the similarities among the microarrays. Data post-spared nerve injury (red circles), chronic constriction injury (green squares) and spinal nerve ligation (blue triangles) are shown with time points as indicated. (B) Venn diagram showing the number of regulated genes meeting fold difference and statistical thresholds in each pain model (spared nerve injury, chronic constriction injury or spinal nerve ligation). (C) Temporal expression patterns of genes regulated in these neuropathic pain models within the DRG. Each gene was normalized to mean 0, SD 1 and subjected to k-means clustering. Increased relative expression level is shown by increasing darkness. (D) Genes related to neurotransmission and neuronal excitability regulated in the DRG. Data shown for each gene are for spared nerve injury (red circles), chronic constriction injury (green squares), or spinal nerve ligation (blue triangles) post-injury. Each plot is on a log2 scale, with the origin at zero equivalent to 1-fold (i.e. non-regulation). The rat gene symbol, maximum difference from origin on the log2 scale, and in parentheses the maximum linear difference, are indicated. Genes are sorted from maximum downregulation to maximum upregulation. SNI = spared nerve injury; CCI = chronic constriction injury; SNL = spinal nerve ligation.

Figure 2

(A) Weighted gene co-expression network analysis/neighbourhood network analysis. KCNS1 was used as a seed and the 30 nearest neighbours were identified, using topological overlap as a measure of connection strength with directly connected genes identified by red links, ion channels identified as purple, receptors and membrane signalling in pink. (B) Heat map showing regulation of the genes in the KCNS1 30 nearest neighbours grouped by hierarchical clustering for differential expression. Red on this plot represents upregulated, with green representing downregulated. To the left are gene names highlighted for function (as above), orange indicates genes have a published link to pain.

Figure 3

(A) Locations of seven genotyped SNPs on coding DNA strand of KCNS1. Coding exons are shown as solid blocks. The SNPs with significant association of pain phenotype are marked. Also marked in yellow is the position of the haplotype block identified in this study. **Most associated SNP, *lesser associated SNP. (B) Association of Val allele of KCNS1 with persistent sciatica after discectomy (Maine chronic lumbar root pain cohort). At one year after surgery, the proportion of patients describing their leg pain as improved falls from 90%, for those with no copies of the Val allele, to 73% of those homozygous for Val. (C) Association of Val allele of KCNS1 with phantom limb pain following leg amputation (Israeli limb amputation pain cohort). Association of Val allele of KCNS1 with proportion of amputee patients reporting no phantom pain falls from 45% for those with no copies of Val to 22% of those homozygous for Val.

Figure 4

Association of Val allele of KCNS1 with acute pain in healthy volunteers (UNC experimental pain cohort). Combined z-score of all experimental assays (18 measures) shows additive correlation of differences in pain thresholds with those homozygous for the Val allele the most sensitive and those homozygous for the Ile allele the least. *P < 0.05.