<i>RGS3</i> and <i>IL1RAPL1</i> missense variants implicate defective neurotransmission in early-onset inherited schizophrenias
Bibliographic record
Abstract
Background Schizophrenia is characterized by hallucinations, delusions and disorganized behaviour. Recessive or X-linked transmissions are rarely described for common psychiatric disorders. We examined the genetics of psychosis to identify rare large-effect variants in patients with extreme schizophrenia. Methods We recruited 2 consanguineous families, each with patients affected by early-onset, severe, treatment-resistant schizophrenia. We performed exome sequencing for all participants. We checked variant rarity in public databases and with ethnically matched controls. We performed in silico analyses to assess the effects of the variants on proteins. Results Structured clinical evaluations supported diagnoses of schizophrenia in all patients and phenotypic absence in the unaffected individuals. Data analyses identified multiple variants. Only 1 variant per family was predicted as pathogenic by prediction tools. A homozygous c.649C > T:p.(Arg217Cys) variant in RGS3 and a hemizygous c.700A > G:p.(Thr234Ala) variant in IL1RAPL1 affected evolutionary conserved amino acid residues and were the most likely causes of phenotype in the patients of each family. Variants were ultra-rare in publicly available databases and absent from the DNA of 400 ethnically matched controls. RGS3 is implicated in modulating sensory behaviour in Caenorhabditis elegans. Variants of IL1RAPL1 are known to cause nonsyndromic X-linked intellectual disability with or without human behavioural dysfunction. Limitations Each variant is unique to a particular family’s patients, and findings may not be replicated. Conclusion Our work suggests that some rare variants may be involved in causing inherited psychosis or schizophrenia. Variant-specific functional studies will elucidate the pathophysiology relevant to schizophrenias and motivate translation to personalized therapeutics.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".