LPHN3 and attention‐deficit/hyperactivity disorder: interaction with maternal stress during pregnancy
Bibliographic record
Abstract
BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous behavioral disorder, complex both in etiology and clinical expression. Both genetic and environmental factors have been implicated, and it has been suggested that gene-environment interactions may play a pivotal role in the disorder. Recently, a significant association was reported between ADHD and LPHN3 (which codes for latrophilin 3), and replicated in independent samples. METHODS: We have examined the association between tag single nucleotide polymorphisms (SNPs) in LPHN3 within the region previously implicated in ADHD. Family based association tests (FBAT) were conducted (n = 380 families) with the categorical diagnosis of ADHD, behavioral and cognitive phenotypes related to ADHD, and response to treatment (given a fixed dose of methylphenidate, 0.5 mg/day). Stratified FBAT analyses, based on maternal smoking and stress during pregnancy, was conducted. RESULTS: Whereas limited association was observed in the total sample, highly significant interaction between four LPHN3 tag SNPs (rs6551665, rs1947274, rs6858066, rs2345039) and maternal stress during pregnancy was noted. Analysis conducted in the sub-group of mothers exposed to minimal stress during pregnancy showed significant associations with ADHD, behavioral and cognitive dimensions related to ADHD, as well as treatment response. Although extensive association was observed with the candidate SNPs, the findings are partially inconsistent with previously published results with the opposite alleles over-transmitted in these studies. CONCLUSIONS: These results provide evidence for the interaction between a genetic and environmental factor independently shown to be associated with ADHD. If confirmed in independent large studies, they may present a step forward in unraveling the complex etiology of ADHD.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".