Microdeletion in a FAAH pseudogene identified in a patient with high anandamide concentrations and pain insensitivity
Bibliographic record
Abstract
The study of rare families with inherited pain insensitivity can identify new human-validated analgesic drug targets. Here, a 66-yr-old female presented with nil requirement for postoperative analgesia after a normally painful orthopaedic hand surgery (trapeziectomy). Further investigations revealed a lifelong history of painless injuries, such as frequent cuts and burns, which were observed to heal quickly. We report the causative mutations for this new pain insensitivity disorder: the co-inheritance of (i) a microdeletion in dorsal root ganglia and brain-expressed pseudogene, FAAH-OUT, which we cloned from the fatty-acid amide hydrolase (FAAH) chromosomal region; and (ii) a common functional single-nucleotide polymorphism in FAAH conferring reduced expression and activity. Circulating concentrations of anandamide and related fatty-acid amides (palmitoylethanolamide and oleoylethanolamine) that are all normally degraded by FAAH were significantly elevated in peripheral blood compared with normal control carriers of the hypomorphic single-nucleotide polymorphism. The genetic findings and elevated circulating fatty-acid amides are consistent with a phenotype resulting from enhanced endocannabinoid signalling and a loss of function of FAAH. Our results highlight previously unknown complexity at the FAAH genomic locus involving the expression of FAAH-OUT, a novel pseudogene and long non-coding RNA. These data suggest new routes to develop FAAH-based analgesia by targeting of FAAH-OUT, which could significantly improve the treatment of postoperative pain and potentially chronic pain and anxiety disorders.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".