DRD2 and PPP1R1B (DARPP-32) polymorphisms independently confer increased risk for autism spectrum disorders and additively predict affected status in male-only affected sib-pair families
Bibliographic record
Abstract
BACKGROUND: The neurotransmitter dopamine (DA) modulates executive functions, learning, and emotional processing, all of which are impaired in individuals with autism spectrum disorders (ASDs). Our previous findings suggest a role for dopamine-related genes in families with only affected males. METHODS: We examined two additional genes which affect DA function, the DRD2 and PPP1R1B (DARPP-32) genes, in a cohort of 112 male-only affected sib-pair families. Selected polymorphisms spanning these genes were genotyped and both family-based and population-based tests were carried out for association analysis. General discriminant analysis was used to examine the gene-gene interactions in predicting autism susceptibility. RESULTS: There was a significantly increased frequency of the DRD2 rs1800498TT genotype (P = 0.007) in affected males compared to the comparison group, apparently due to over-transmission of the T allele (P = 0.0003). The frequency of the PPP1R1B rs1495099CC genotype in affected males was also higher than that in the comparison group (P = 0.002) due to preferential transmission of the C allele from parents to affected children (P = 0.0009). Alleles rs1800498T and rs1495099C were associated with more severe problems in social interaction (P = 0.0002 and P = 0.0016, respectively) and communication (P = 0.0004 and P = 0.0046), and increased stereotypic behaviours (P = 0.0021 and P = 0.00072). General discriminant analysis found that the DRD2 and PPP1R1B genes additively predicted ASDs (P = 0.00011; Canonical R = 0.26) and explain ~7% of the variance in our families. All findings remained significant following corrections for multiple testing. CONCLUSION: Our findings support a role for the DRD2 and PPP1R1B genes in conferring risk for autism in families with only affected males and show an additive effect of these genes towards prediction of affected status in our families.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".