Alopecia areata is characterized by dysregulation in systemic type 17 and type 2 cytokines, which may contribute to disease‐associated psychological morbidity
Bibliographic record
Abstract
BACKGROUND: T cells dominate hair follicle pathogenesis, but the specific mechanisms driving hair loss are not fully understood. OBJECTIVES: To provide a detailed insight into the systemic cytokine signature associated with AA, and to assess the association between cytokines and depression. METHODS: We conducted multiplex analysis of plasma cytokines from patients with AA, patients with psoriatic arthritis (PsA) and healthy controls. We used the Hospital Anxiety and Depression Scale (HADS) to assess the occurrence of depression and anxiety in our cohort. RESULTS: Our analysis identified a systemic inflammatory signature associated with AA, characterized by elevated levels of interleukin (IL)-17A, IL-17F, IL-21 and IL-23 indicative of a type 17 immune response. Circulating levels of the type 2 cytokines IL-33, IL-31 and IL-17E (IL-25) were also significantly increased in AA. In comparison with PsA, AA was associated with higher levels of IL-17F, IL-17E and IL-23. We hypothesized that circulating inflammatory cytokines may contribute to wider comorbidities associated with AA. Our assessment of psychiatric comorbidity in AA using HADS scores showed that 18% and 51% of people with AA experienced symptoms of depression and anxiety, respectively. Using linear regression modelling, we identified that levels of IL-22 and IL-17E are positively and significantly associated with depression. CONCLUSIONS: T-cell response. An immunological mechanism might contribute directly to the depression observed in people with AA.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".