Inhibition of the kinase WNK1/HSN2 ameliorates neuropathic pain by restoring GABA inhibition
Bibliographic record
Abstract
HSN2is a nervous system predominant exon of the gene encoding the kinase WNK1 and is mutated in an autosomal recessive, inherited form of congenital pain insensitivity. The HSN2-containing splice variant is referred to as WNK1/HSN2. We created a knockout mouse specifically lacking theHsn2exon ofWnk1 Although these mice had normal spinal neuron and peripheral sensory neuron morphology and distribution, the mice were less susceptible to hypersensitivity to cold and mechanical stimuli after peripheral nerve injury. In contrast, thermal and mechanical nociceptive responses were similar to control mice in an inflammation-induced pain model. In the nerve injury model of neuropathic pain, WNK1/HSN2 contributed to a maladaptive decrease in the activity of the K(+)-Cl(-)cotransporter KCC2 by increasing its inhibitory phosphorylation at Thr(906)and Thr(1007), resulting in an associated loss of GABA (γ-aminobutyric acid)-mediated inhibition of spinal pain-transmitting nerves. Electrophysiological analysis showed that WNK1/HSN2 shifted the concentration of Cl(-)such that GABA signaling resulted in a less hyperpolarized state (increased neuronal activity) rather than a more hyperpolarized state (decreased neuronal activity) in mouse spinal nerves. Pharmacologically antagonizing WNK activity reduced cold allodynia and mechanical hyperalgesia, decreased KCC2 Thr(906)and Thr(1007)phosphorylation, and restored GABA-mediated inhibition (hyperpolarization) of injured spinal cord lamina II neurons. These data provide mechanistic insight into, and a compelling therapeutic target for treating, neuropathic pain after nerve injury.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".