A Point Mutation in a lincRNA Upstream of GDNF Is Associated to a Canine Insensitivity to Pain: A Spontaneous Model for Human Sensory Neuropathies
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Bibliographic record
Abstract
Human Hereditary Sensory Autonomic Neuropathies (HSANs) are characterized by insensitivity to pain, sometimes combined with self-mutilation. Strikingly, several sporting dog breeds are particularly affected by such neuropathies. Clinical signs appear in young puppies and consist of acral analgesia, with or without sudden intense licking, biting and severe self-mutilation of the feet, whereas proprioception, motor abilities and spinal reflexes remain intact. Through a Genome Wide Association Study (GWAS) with 24 affected and 30 unaffected sporting dogs using the Canine HD 170K SNP array (Illumina), we identified a 1.8 Mb homozygous locus on canine chromosome 4 (adj. p-val = 2.5x10-6). Targeted high-throughput sequencing of this locus in 4 affected and 4 unaffected dogs identified 478 variants. Only one variant perfectly segregated with the expected recessive inheritance in 300 sporting dogs of known clinical status, while it was never present in 900 unaffected dogs from 130 other breeds. This variant, located 90 kb upstream of the GDNF gene, a highly relevant neurotrophic factor candidate gene, lies in a long intergenic non-coding RNAs (lincRNA), GDNF-AS. Using human comparative genomic analysis, we observed that the canine variant maps onto an enhancer element. Quantitative RT-PCR of dorsal root ganglia RNAs of affected dogs showed a significant decrease of both GDNF mRNA and GDNF-AS expression levels (respectively 60% and 80%), as compared to unaffected dogs. We thus performed gel shift assays (EMSA) that reveal that the canine variant significantly alters the binding of regulatory elements. Altogether, these results allowed the identification in dogs of GDNF as a relevant candidate for human HSAN and insensitivity to pain, but also shed light on the regulation of GDNF transcription. Finally, such results allow proposing these sporting dog breeds as natural models for clinical trials with a double benefit for human and veterinary medicine.
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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 | 0.000 | 0.006 |
| 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 it