Sexual Dimorphism in the Th17 Signature of Ankylosing Spondylitis
Bibliographic record
Abstract
OBJECTIVE: To identify an immunologic basis for the male sex bias in ankylosing spondylitis (AS). METHODS: Cohorts of male and female patients with AS and age- and sex-matched healthy control subjects were selected, and the levels of serum cytokines (interferon-γ [IFNγ], tumor necrosis factor α, interleukin-17A [IL-17A], and IL-6) were examined by enzyme-linked immunosorbent assay, the frequencies of Th1 and Th17 cells were assessed by flow cytometry, and whole blood gene expression was analyzed using both microarray and NanoString approaches. RESULTS: The frequency of IL-17A and Th17 cells, both of which are key factors in the inflammatory Th17 axis, was elevated in male patients with AS but not in female patients with AS. In contrast, AS-associated alterations in the Th1 axis, such as the frequency of IFNγ and Th1 cells in serum, were independent of a patient's sex. Results of microarray analysis supported an altered Th17 axis in male patients, with a specific increase in IL17RA. In addition, male and female patients with AS displayed shared gene expression patterns, while male patients with AS had additional alterations in gene expression that were not seen in female patients with AS. The differential sex-related immune profiles were independent of HLA-B27 status, clinical disease activity (as measured by the Bath Ankylosing Spondylitis Disease Activity Index), or treatment (with nonsteroidal antiinflammatory drugs or biologic agents), implicating intrinsic sexual dimorphism in AS. CONCLUSION: The results of this study demonstrate distinct sexual dimorphism in the activation status of the immune system in patients with AS, particularly in the Th17 axis. This dimorphism could underlie sex-related differences in the clinical features of AS and could provide a rationale for sex-specific treatment of AS.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".