NESPRED-Study 2|The role of neurochemical signatures of stress and attachment styles in recurrent depression
Bibliographic record
Abstract
The aim of this study is to identify the neurochemical signatures of individual variations in attachment styles and stress responses and their role as risk factors for recurrent MDD and its subtypes. Maladaptive attachment styles (Bowlby, 1977) and responses to stressful life events (Brown & Harris, 1989) have been established as risk factors for MDD. Morning cortisol and cortisol awakening response, as neurochemical signatures of the stress response, were found to be a reproducible predictor of recurrence risk in MDD. Yet, the role of the endogenous mu-opioid (Jelen et al., 2022), oxytocin, and adrenergic systems, which together with cortisol, play a key role in the stress response, have been under-investigated in MDD. Furthermore, the mu-opioid system together with oxytocin (Insel & Young 2001, Depue & Morrone-Strupinsky 2005, Johnson & Dunbar 2016) play a crucial role in attachment styles, but have not been investigated to stratify MDD pathophysiology. We will assess sensitivity to pain measured using the well validated McGill Pain Questionnaire-Short Form (Melzack, 1987) after pain induction with a blood pressure cuff (Maurset et al., 1991). This is a validated measure of low endogenous mu-opioid function, shown to be associated with high anger expression tendencies and low likelihood of benefitting from exogenous opioids for pain (Burns et al., 2017). This is relevant, because of the emerging evidence for the opioid system (Browne et al., 2020) for developing new treatments for depression whilst tackling the addiction to exogenous opioids overprescribed for chronic pain. There is very little research on the role of the endogenous opioid system in vulnerability to depression and its potential for subtyping people with MDD. Furthermore, there is strong evidence for the relevance of the mu-opioid system in attachment styles (Nummenmaa et al., 2015) which we assess with the Personal Style Inventory-II and its related constructs of striving for autonomy and sociotropy. We have previously shown selective associations between individual differences in attachment styles, particularly a factor loading onto defensive separation and need for control, with subgenual cingulate fMRI activation using our fMRI paradigm to assess self-blaming biases (Lythe et al., 2020).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".