Depressive Symptom Heterogeneity and Inflammation: The Moderating Role of Early-Life Trauma
Bibliographic record
Abstract
Despite the high prevalence rates of depression, particularly among young adults, current treatments remain suboptimal, partly owing to the complex and heterogeneous nature of the disorder. While some individuals with depression display elevated inflammation, this is not consistently reported and may depend on the specific symptoms expressed. Moreover, individuals exposed to traumatic events may be more vulnerable to inflammation and mood disorders. In the current study young adults (N=210) completed baseline questionnaires assessing adverse early life experiences and depressive symptoms, provided blood samples to measure C-reactive protein (CRP) levels, and were assigned to either a control (n=106) or a stressor (n=104) task. CRP levels were positively correlated with both typical (p=0.02) and atypical depression (p=0.03), as well as total trauma (p=0.02), general trauma (p=0.012), and physical abuse (p=0.02) within the stress group. Notably, upon assessing specific symptoms of depression, somatic features including sleep and fatigue correlated with higher CRP levels. Additionally, the relationship between CRP levels and depressive symptoms was moderated by experiences of sexual abuse (p=0.03). These findings suggest that the CRP-depression link may be driven by somatic features of depression, and that exposure to early life trauma may play an important role in modulating this relationship. Understanding the relationship between adverse early life experiences, inflammation, and specific depressive symptoms can help inform an integrated approach that combines biological, psychological, and social factors to improve both prevention and treatment outcomes for depression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".