Impact of Having Family History of Psoriasis or Psoriatic Arthritis on Psoriatic Disease
Bibliographic record
Abstract
OBJECTIVE: Psoriatic arthritis (PsA) has a genetic background. Approximately 40% of patients with psoriasis or PsA have a family history of psoriasis or PsA, which may affect disease features. The aim of this study was to assess the effects of family history of psoriasis and PsA on disease phenotypes. METHODS: Data from 1,393 patients recruited in the longitudinal, multicenter Psoriatic Arthritis International Database were analyzed. The effects of family history of psoriasis and/or PsA on characteristics of psoriasis and PsA were investigated using logistic regression. RESULTS: A total of 444 patients (31.9%) had a family history of psoriasis and/or PsA. These patients were more frequently women, had earlier onset of psoriasis, more frequent nail disease, enthesitis, and deformities, and less frequently achieved minimal disease activity. Among 444 patients, 335 only had psoriasis in their family, 74 had PsA, and 35 patients were not certain about having PsA and psoriasis in their family, so they were excluded from further analysis. In the multivariate analysis, family history of psoriasis was associated with younger age at onset of psoriasis (odds ratio [OR] 0.976) and presence of enthesitis (OR 1.931), whereas family history of PsA was associated with lower risk of plaque psoriasis (OR 0.417) and higher risk of deformities (OR 2.557). Family history of PsA versus psoriasis showed increased risk of deformities (OR 2.143) and lower risk of plaque psoriasis (OR 0.324). CONCLUSION: Family history of psoriasis and PsA impacts skin phenotypes, musculoskeletal features, and disease severity. The link between family history of psoriasis/PsA and pustular/plaque phenotypes may point to a different genetic background and pathogenic mechanisms in these subsets.
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 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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".