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Record W2940378003 · doi:10.1111/bjd.18008

Alopecia areata is characterized by dysregulation in systemic type 17 and type 2 cytokines, which may contribute to disease‐associated psychological morbidity

2019· article· en· W2940378003 on OpenAlexaff
Kym A. Bain, Elizabeth S. McDonald, Fiona Moffat, Mauro Tutino, Madhura Castelino, Anne Barton, Jonathan Cavanagh, Umer Zeeshan Ijaz, Stefan Siebert, Iain B. McInnes, Annika Åstrand, Simon Holmes, Simon Milling

Bibliographic record

VenueBritish Journal of Dermatology · 2019
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsInstitute of Infection and Immunity
FundersVersus ArthritisMedical Research ScotlandAlopecia UKAstraZeneca
KeywordsAlopecia areataMedicineImmune dysregulationHospital Anxiety and Depression ScaleDepression (economics)Alopecia universalisImmunologyPathogenesisCytokineAnxietyInternal medicineCohortImmune systemPsychiatry

Abstract

fetched live from OpenAlex

Alopecia areata (AA) is a common autoimmune disease, causing patchy hair loss that can progress to involve the entire scalp (totalis) or body (universalis). CD8+NKG2D+ T cells dominate hair follicle pathogenesis, but the specific mechanisms driving hair loss are not fully understood. To provide a detailed insight into the systemic cytokine signature associated with AA, and to assess the association between cytokines and depression. 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. 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. Our data highlight changes in both type 17 and type 2 cytokines among people with AA, suggesting that complex systemic cytokine profiles may contribute both to the pathogenesis of AA and to the associated depression. What's already known about this topic? NKG2D+CD8+ T cells cause hair loss in alopecia areata (AA) but the immunological mechanisms underlying the disease are not fully understood. AA is associated with changes in levels of interleukin (IL)‐6, tumour necrosis factor‐α, IL‐1β and type 17 cytokines. Psychiatric comorbidity is common among people with AA. What does this study add? People with AA have increased plasma levels of the type 2 cytokines IL‐33, IL‐31 and IL‐17E (IL‐25), in addition to the type 17 cytokines IL‐17A, IL‐21, IL‐23 and IL‐17F. Levels of IL‐17E and IL‐22 positively predict depression score. What is the translational message? AA is associated with increased levels of multiple inflammatory cytokines, implicating both type 17‐ and type 2 immune pathways. Our data indicate that therapeutic strategies for treating AA may need to address the underlying type 17‐ and type 2 immune dysregulation, rather than focusing narrowly on the CD8+ 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.014
GPT teacher head0.285
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations92
Published2019
Admission routes1
Has abstractyes

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