5-HTTLPR polymorphism in bulimia nervosa
Bibliographic record
Abstract
Several lines of research have found that genes in the serotonergic system may cause susceptibility to eating disorders (EDs). In particular, functional polymorphisms of the serotonin transporter gene (5-HTT) have been suspected to play a role in the pathogenesis of eating disorders. Several studies have examined the association between the 5-HTTLPR polymorphism and bulimia nervosa (BN). The results of these investigations have been unclear. The aims of this meta-analysis were to clarify the association between BN and 5-HTTLPR using statistical models not used by previous meta-analyses, and extend upon previous meta-analyses by including new samples. PsychINFO, ISI, and PubMed databases were searched for studies published up to May 2011. Ultimately, six case-control samples were included. Data were pooled using dominant and additive models. Both models showed a nonsignificant association between the 5-HTTLPR polymorphism and BN. However, this does not detract from recent research suggesting that the 5-HTTLPR polymorphism may be responsible for the phenotypic variability in the psychopathological symptoms observed in patients with BN. Future research should examine the association of BN with 5-HTTLPR using the recently proposed triallelic model.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".