<i>CCR5</i>-Δ32 polymorphism: a possible protective factor for post-stroke depressive symptoms
Bibliographic record
Abstract
Background: A naturally occurring loss-of-function mutation in the gene for C-C chemokine receptor type 5 (CCR5-Δ32) has recently been reported as a protective factor in post-stroke motor and cognitive recovery. We sought to examine whether this mutation also prevented the development of depressive symptoms up to 2 years after a stroke. Methods: Participants were survivors of a first-ever mild to moderate ischemic stroke or transient ischemic attack from the TABASCO prospective study who underwent a 3 T MRI at baseline and were examined by a multiprofessional team 6, 12 and 24 months after the event, including an evaluation of depressive symptoms using the Geriatric Depression Scale. Results: CCR5-Δ32 status and a baseline depression evaluation were available for 435 patients. Compared with noncarriers, CCR5-Δ32 carriers (16.1%) had fewer depressive symptoms at admission (p = 0.035) and at 6 months (p < 0.001), 12 months (p < 0.001) and 24 months (p = 0.006) after the index event. This association remained significant at 6 and 12 months after adjustment for age, sex, education, antidepressant use, ethnicity and the presence of cortical infarcts. These findings were more robust in women. Compared to baseline, depressive symptoms in CCR5-Δ32 noncarriers tended to remain stable or grow worse over time, but in CCR5-Δ32 carriers, symptoms tended to improve. Limitations: A limitation of this study was the exclusion of patients who had a severe stroke or who had pre-stroke depression. Conclusion: Carriers of the CCR5-Δ32 allele had a lower tendency to develop depressive symptoms post-stroke, and this phenomenon was more prominent in women. These findings could have clinical implications; they suggest a mechanism-based treatment target for post-stroke depression. Drugs mimicking this loss-of-function mutation exist and could serve as a novel antidepressant therapy.
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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".