The Role of Reactive Oxygen Species in the Pathogenesis of Alopecia Areata: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Alopecia areata (AA) is a T-cell-mediated autoimmune disease that significantly impacts patient quality of life. The breakdown of hair follicle immune privilege underlies AA pathogenesis. However, the precise mechanism of this breakdown remains unclear. This study investigates the potential role of reactive oxygen species in AA pathogenesis. SUMMARY: A systematic review and meta-analysis were conducted on observational studies and randomized controlled trials from 2000 to 2024. Studies included AA patients and measured oxidative stress index (OSI), malondialdehyde (MDA), superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), or paraoxonase-1 (PON1). Extracted data were analyzed using the Cochrane risk-of-bias tool and random-effects models. The review included 21 studies with 743 AA patients. OSI was elevated in AA patients (effect size = 1.58, 95% CI: 0.31-2.68, p = 0.00068). MDA levels were also elevated (effect size = 1.60, 95% CI: 0.43-2.6, p = 0.00023), while SOD (effect size = -0.97, 95% CI: -1.65 to -0.30, p = 0.00066) and GSH-Px (effect size = -1.41, 95% CI: -2.28 to -0.53, p = 0.00068) activities were reduced. PON1 levels showed no significant difference (effect size = -3.56, 95% CI: -8.63 to 1.51, p = 0.051). KEY MESSAGES: The elevated OSI and MDA, and decreased antioxidant activity in AA patients suggest a substantial role for reactive oxygen species and oxidative stress in AA pathogenesis, highlighting oxidative stress as a potential target for therapeutic intervention. These results underscore the importance of oxidative stress in AA and support further research into antioxidant-based therapies.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.029 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".