Systems genetic and pharmacological analysis identifies candidate genes underlying mechanosensation in the von Frey test
Bibliographic record
Abstract
Mechanical sensitivity is commonly affected in chronic pain and other neurological disorders. To discover mechanisms of individual differences in punctate mechanosensation, we performed quantitative trait locus (QTL) mapping of the response to von Frey monofilament stimulation in BXD recombinant inbred (BXD) mice. Significant loci were detected on mouse chromosome (Chr) 5 and 15, indicating the location of underlying polymorphisms that cause heritable variation in von Frey response. Convergent evidence from public gene expression data implicates candidate genes within the loci: von Frey thresholds were strongly correlated with baseline expression of Cacna2d1, Ift27 and Csnk1e in multiple brain regions of BXD strains. Systemic gabapentin and PF-670462, which target the protein products of Cacna2d1 and Csnk1e, respectively, significantly increased von Frey thresholds in a genotype-dependent manner in progenitors and BXD strains. Real-time polymerase chain reaction confirmed differential expression of Cacna2d1 and Csnk1e in multiple brain regions in progenitors and showed differential expression of Cacna2d1 and Csnk1e in the dorsal root ganglia of the progenitors and BXD strains grouped by QTL genotype. Thus, linkage mapping, transcript covariance and pharmacological testing suggest that genetic variation affecting Cacna2d1 and Csnk1e may contribute to individual differences in von Frey filament response. This study implicates Cacna2d1 and Ift27 in basal mechanosensation in line with their previously suspected role in mechanical hypersensitivity. Csnk1e is implicated for von Frey response for the first time. Further investigation is warranted to identify the specific polymorphisms involved and assess the relevance of these findings to clinical conditions of disturbed mechanosensation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".