Exploring the Genetic Landscape of Psoriatic Arthritis: A Narrative Review of Recent Genomic Studies
Bibliographic record
Abstract
The recent availability of large-scale genomic datasets in psoriatic disease, combined with advances in molecular tools, next-generation genomic technologies, and informatics, has led to a better understanding of the genomic basis of psoriatic arthritis (PsA). Although no current genetic tests exist for the management of PsA, the potential for early diagnosis and treatment orientation through genomic studies remains a source of continued optimism. Ongoing studies aim to advance the stratification, prognosis, and pharmacogenomics of PsA. This review highlights recent advances in the genomics of PsA, focusing on genomic variants that may become clinically actionable. We will discuss the importance of elucidating family history, highlight potential clinically significant psoriatic genes, emphasize genetic variants that may identify PsA among patients with psoriasis, and explore the emerging roles of transcript profiling, single-cell sequencing, and spatial omics in PsA.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".