Association testing of vasopressin receptor 1a microsatellite polymorphisms in non‐clinical autism spectrum phenotypes
Bibliographic record
Abstract
Variation in the AVPR1a gene, which codes for a receptor for the neurohormone vasopressin, has been found to relate to autism risk. Interestingly, variation in this gene also relates to differences in social behaviour in non-clinical populations. Variation in this gene may affect expression of AVPR1a receptors in brain areas involved in social behaviour. Here, we tested whether AVPR1a variation was associated with Autism Quotient (AQ) scores, a questionnaire that measures non-clinical manifestations of autism, in a population of 873 healthy university students. The AVPR1a RS1 and RS3 microsatellites were examined, and variants were categorized as "long" or "short". The RS3 long/long genotype was significantly associated with a higher AQ score (i.e., a more autistic-like phenotype) for the combined population and for females only. Further examination showed that this relationship was due to a specific RS3 variant, termed the "target allele", which previous research has linked to reduced altruism and increased marital problems in healthy individuals. We also observed that the relationship between RS3 genotype and AQ score was mainly due to the "attention switching" (the ability to shift attention from one task to another) component of the questionnaire; this ability is commonly impaired in autism spectrum disorders. Overall, our study establishes continuity between the existing AVPR1a research in clinical and non-clinical populations. Our results suggest that vasopressin may exert its effects on social behaviour in part by modulating attentional focus between social and non-social cues. Autism Res 2017, 10: 750-756. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".