Sex-specific interaction effects of Syntaxin 1A coexpression network and childhood trauma on adult depressive symptoms
Bibliographic record
Abstract
BACKGROUND: Disruptions in synaptic function and exposure to early life trauma are both implicated in the development of depression, though the underlying mechanisms remain poorly understood. METHODS: To investigate this relationship, we developed an expression-based polygenic score (ePRS) that captures individual variations in the expression of genes co-expressed with the synaptic protein Syntaxin 1A (STX1A) in the prefrontal cortex (PFC). This polygenic score allows us to explore the impact of variations on synaptic function and childhood trauma on the susceptibility to depressive symptoms in adulthood. FINDINGS: Our findings indicate that the PFC-ePRS-STX1A score moderates the effects of childhood trauma on the diagnosis of depression in adult females from the UK Biobank (Logistic regression, β = -0.150, p = 0.001, N = 72,812). A similar result was found in an independent cohort (ALSPAC), where PFC-ePRS-STX1A moderated the effects of childhood trauma on depressive symptoms in younger adult females, confirming the sex-specific moderation effect (GEE analysis, ages 22-23, β = -1.063, p = 0.0046, N = 1846). Functional enrichment analysis of the STX1A-coexpressed network revealed key biological processes related to protein synthesis, with 25.8% associated gene products localised to synaptic components at both pre and postsynaptic sites. INTERPRETATION: This highlights the critical role of synaptic plasticity function in the PFC in shaping the long-term effects of early trauma on depression. Our methodology and results offer valuable insights into individual vulnerability to depression following early trauma and highlight synaptic function as a potential target for interventions aimed at mitigating depression risk. FUNDING: JPB Foundation; Hope for Depression Research Foundation; CAPES; Fonds de recherche du Québec, and CIHR.
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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 | 0.000 |
| 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) | 0.003 | 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".