Refining psychiatric phenotypes for response to treatment: Contribution of LPHN3 in ADHD
Bibliographic record
Abstract
Attention deficit/hyperactivity disorder (ADHD) is a heterogeneous disorder characterized by inappropriate levels of attention, hyperactivity, and impulsivity. Although a strong genetic component to the disorder has been established, the molecular genetic underpinnings of this disorder remain elusive. Recently, several studies have reported an association between polymorphisms within the latrophilin 3 gene (LPHN3) and ADHD. Interestingly, the same single-nucleotide polymorphism conferring susceptibility to ADHD has also been found to predict efficacy of stimulant medication in children. The main objectives of the current article are: (i) To tackle the phenotype heterogeneity issue in ADHD by defining an objective and quantitative measure of response to treatment in a sample of ADHD children based on a hand held automatic device (Actiwatch) and (ii) to use this measure to reproduce for the first time the association between LPHN3 variants and response to methylphenidate (MPH) using a double-blind, placebo-controlled crossover experimental design. The results of our study confirm the hypothesis that LPHN3 is associated with response to MPH in ADHD children. Although this will require further validation, our work suggests that the use of an objective measure of response to treatment, such as the change in the child's motor activity measured by Actiwatch, has the potential to uncover genetic association signals that in some conditions might not be obtained using more subjective measures, such as the clinical consensus rating, for example.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".