Serum amyloid P component level is associated with clinical response to escitalopram treatment in patients with major depressive disorder
Bibliographic record
Abstract
Serum amyloid P component (SAP) is a universal constituent of human amyloid deposits, which has been implicated in Alzheimer's disease and major depressive disorder (MDD). However, the relationship between SAP level and depression severity remains obscure. The aims of this study were to investigate how SAP is involved in depression and to explore the association between SAP level and antidepressant treatment response. Patients with MDD (n = 85) who received escitalopram monotherapy for 8-12 weeks were selected from a multicenter open-label randomized clinical trial. The same number of healthy controls was recruited. Depression severity was measured according to the Hamilton Depression Rating Scale (HAMD-17) at baseline and weeks 4, 8, and 12. The plasma levels of SAP were measured at baseline, week 2 and week 12. As a result, baseline levels of SAP were significantly higher in depressed patients than in control subjects (p < 0.001). SAP levels at baseline were negatively associated with depression severity after escitalopram treatment (p < 0.05), and the changes in SAP levels from baseline to week 12 were highly correlated with the severity of depressive symptoms based on the HAMD-17 score (p < 0.05). Interestingly, treatment with escitalopram significantly decreased the plasma levels of SAP in females, but not in males. Altogether, our results suggest that SAP not only involved in the pathobiology of depression but also mediates the action of antidepressant medications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.000 | 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".