Differential Allelic Expression of HTR1B in Suicide Victims: Genetic and Epigenetic Effect of the <b><i>Cis</i></b>-Acting Variants
Bibliographic record
Abstract
OBJECTIVES: In the present study, we tested the allelic imbalance of the C861G single nucleotide polymorphism (SNP) of HTR1B in the frontal cortex of suicide victims. METHODS: The study was conducted using 3 sets of samples. First, C861G allele-specific mRNA levels in the frontal cortex were compared between suicide (n = 13) and nonsuicide controls (n = 13) from the Stanley Medical Research postmortem brain collection. Second, we tested common variants in the HTR1B promoter for linkage disequilibrium (LD) with the C861G variant in an unrelated sample of suicide attempters (SA; n = 38) and non-SA (NSA; n = 42). Finally, we performed a family-based association study of the C861G and promoter variants in 162 nuclear families using suicidal behavior severity scores as phenotype. RESULTS: We observed no alterations in the C/G expression ratio in suicide victims compared to nonsuicide controls (p = 0.370). When comparing the LD between the C861G and cis-acting SNPs, we did not find any differences in SA and NSA. There was no association between preferential transmission of cis-acting SNPs and suicidal behavior severity scores in both maternal and paternal meiosis. CONCLUSIONS: We found several promoter variants in LD that may potentially influence the allelic imbalance in the C861G variant. However, no evidence of allelic imbalance nor parent-of-origin effects of the C861G variant was observed in suicidal behavior. Further research is required to assess this marker in larger cohorts.
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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 | 0.000 |
| 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".