Multiple chronic pain states are associated with a common amino acid–changing allele in KCNS1
Bibliographic record
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".