<i>ANKH</i>and Susceptibility to and Severity of Ankylosing Spondylitis
Bibliographic record
Abstract
OBJECTIVE: Unconfirmed reports describe association of ankylosing spondylitis (AS) with several candidate genes including ANKH. Cellular export of inorganic pyrophosphate is regulated by the ANK protein, and mutant mice (ank/ank), which have a premature stop codon in the 3' end of the ank gene, develop severe ankylosis. We tested the association between single-nucleotide polymorphisms (SNP) in these genes and susceptibility to AS in a population of patients with AS. We investigated the role of these genes in terms of functional (BASFI) and metrological (BASMI) measures, and the association with radiological severity (mSASSS). METHODS: Our study was conducted on 355 patients with AS and 95 ethnically matched healthy controls. AS was defined according to the modified New York criteria. Four SNP in ANKH (rs27356, rs26307, rs25957, and rs28006) were genotyped. Association analysis was performed using Cochrane-Armitage and linear regression tests for dichotomous and quantitative variables. Analyses of Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), BASFI, and mSASSS were controlled for sex and disease duration. RESULTS: None of the 4 markers showed significant single-locus disease associations (p > 0.05), suggesting that ANKH was not a major determinant of AS susceptibility in our population. No association was observed between these SNP and age at symptom onset, BASDAI, BASFI, BASMI, or mSASSS. CONCLUSION: These results confirm data in white Europeans that ANKH is probably not a major determinant of susceptibility to AS. ANKH polymorphisms do not markedly influence AS disease severity, as measured by BASMI and mSASSS.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 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".