Rare Synaptogenesis-Impairing Mutations in SLITRK5 Are Associated with Obsessive Compulsive Disorder
Bibliographic record
Abstract
Obsessive compulsive disorder (OCD) is substantially heritable, but few molecular genetic risk factors have been identified. Knockout mice lacking SLIT and NTRK-Like Family, Member 5 (SLITRK5) display OCD-like phenotypes including serotonin reuptake inhibitor-sensitive pathologic grooming, and corticostriatal dysfunction. Thus, mutations that impair SLITRK5 function may contribute to the genetic risk for OCD. We re-sequenced the protein-coding sequence of the human SLITRK5 gene (SLITRK5) in three hundred and seventy seven OCD subjects and compared rare non-synonymous mutations (RNMs) in that sample with similar mutations in the 1000 Genomes database. We also performed in silico assessments and in vitro functional synaptogenesis assays on the Slitrk5 mutations identified. We identified four RNM's among these OCD subjects. There were no significant differences in the prevalence or in silico effects of rare non-synonymous mutations in the OCD sample versus controls. Direct functional testing of recombinant SLITRK5 proteins found that all mutations identified in OCD subjects impaired synaptogenic activity whereas none of the pseudo-matched mutations identified in 1000 Genomes controls had significant effects on SLITRK5 function (Fisher's exact test P = 0.028). These results demonstrate that rare functional mutations in SLITRK5 contribute to the genetic risk for OCD in human populations. They also highlight the importance of biological characterization of allelic effects in understanding genotype-phenotype relationships as there were no statistical differences in overall prevalence or bioinformatically predicted effects of OCD case versus control mutations. Finally, these results converge with others to highlight the role of aberrant synaptic function in corticostriatal neurons in the pathophysiology of OCD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".