Interaction between tryptophan hydroxylase I polymorphisms and childhood abuse is associated with increased risk for borderline personality disorder in adulthood
Bibliographic record
Abstract
INTRODUCTION: Borderline personality disorder (BPD) is a severe disorder with high morbidity and mortality, but unknown etiology. Childhood abuse has been proposed as an etiological factor, but the mechanism by which an abuse history could influence the risk for BPD has not been determined. The aim of this study was to determine whether the tryptophan hydroxylase 1 (TPH1) gene is related to BPD in a clinical sample, and whether TPH1 genotypes or haplotypes moderate the relationship between abuse history and BPD. METHODS: Three hundred and ninety-eight patients diagnosed with mood disorders were genotyped for TPH1 G-6526A promoter polymorphism (rs4537731) and the A218C intron 7 polymorphism (rs1800532) and a set of ancestry informative markers, assessed for Diagnostic and Statistical Manual of Mental Disorders, 4th edition diagnoses, and assessed for a history of physical and sexual abuse. RESULTS: Patients with a diagnosis of BPD were more likely to be risk allele carriers (A alleles at both loci) than the non-BPD group. Logistic regression analysis predicting BPD diagnosis with both single-nucleotide polymorphisms and haplotypes showed significant interaction effects between genotype and abuse history. Poisson regression predicting the number of BPD diagnostic criteria met with the same predictor set also included a significant interaction term. Risk allele carriers with a history of abuse had an increased likelihood of a BPD diagnosis. CONCLUSION: Variation in TPH1 may increase risk for developing BPD as a result of childhood abuse. Elements of BPD pathology may be due in part to a genetically influenced serotonergic dysfunction, which in turn may lead to a differential response to environmental stressors.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".