Associations between the <b><i>LEP</i></b> -2548G/A Promoter and Baseline Weight and between <b><i>LEPR</i></b> Gln223Arg and Lys656Asn Variants and Change in BMI <b><i>z</i></b> Scores in Arab Children and Adolescents Treated with Risperidone
Bibliographic record
Abstract
Data on baseline (antipsychotics-naïve) age, weight, and height, and change in these at 3 subsequent follow-up time points up to 313.6 days (95% CI 303.5–323.7) were collected from 181 risperidone-treated children and adolescents (mean age 12.58 years, SD 4.99, range 2.17–17.7) attending a pediatric neurology clinic in Saudi Arabia. Owing to differences in genotypic distributions in the subsamples, results are reported for the white Arab population (n = 144). Age- and gender-normed body mass index (BMI)-standardized z scores (BMI z) were calculated (LMSgrowth program). Linear regression was performed for baseline weight and BMI z, while change in BMI z was assessed using random effects ordered logistic regression. The following single nucleotide polymorphisms (SNPs) were analyzed: rs7799039 in the LEP promoter, rs1805094 (previously rs8179183), rs1137100 and rs1137101 in the LEPR, and rs1414334 in HTR2C. We found a nominally significant association between rs7799309 and baseline weight, adjusting for height, age, gender, and diagnosis (A/G, p = 0.035, β = –3.62 vs. G/G). The rs1137101 (G/G, p = 0.018, odds ratio [OR] = 4.13 vs. A/A) and rs1805094 C allele carriers (p = 0.019, OR = 0.51) showed nominally significant associations with change in BMI z categories. Our data support and replicate previous relevant associations for these variants (including with weight gain when on risperidone), whilst being the first report of such associations in patients of Arab ethnicity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".