The influence of family structure, the TPH2 G‐703T and the 5‐HTTLPR serotonergic genes upon affective problems in children aged 10–14 years
Bibliographic record
Abstract
BACKGROUND: Both genetic and psychosocial risk factors influence the risk for depression in development. While the impacts of family structure and of serotonergic polymorphisms upon individual differences for affective problems have been investigated separately, they have never been considered together in a gene-environment interplay perspective. METHODS: We examined the effects of family structure and two serotonergic polymorphisms (the TPH2 G-703T and the 5-HTTLPR) upon depressive symptoms assessed by the new CBCL/6-18 DSM-oriented Affective Problems scale in a general population sample of 607 Italian children aged 10-14 years. RESULTS: Belonging to 'one-parent' families, the TPH2 G-703T 'G variant', and the 5-HTTLPR 'short' alleles were associated - both alone and in apparent gene-by-environment interaction - with higher Affective Problems scores. As predicted by quantitative genetics theory, both polymorphisms contributed with a small effect size, while 'family structure' had a moderate effect size. CONCLUSIONS: A putative hazard factor impinging on individual risk at the family-wide level, namely family structure, appears to act interactively with two pivotal serotonergic genes in heightening risk for Affective Problems. Although it remains to be demonstrated that belonging to a one- rather than a two-parent family has true environmental causal effects on Affective Problems, these data may contribute to identify/prevent risk for depression in childhood.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".