Angiotensin-Converting Enzyme Gene Does Not Contribute to Genetic Susceptibility to Systemic Sclerosis in European Caucasians
Bibliographic record
Abstract
OBJECTIVE: To determine whether angiotensin-converting enzyme (ACE) polymorphisms including I/D and 2 single-nucleotide polymorphisms (SNP) affect susceptibility to systemic sclerosis (SSc) in a large French Caucasian population. METHODS: A case-control study was performed in 494 patients with SSc and 280 healthy controls for I/D polymorphism. Two supplementary exonic SNP of ACE gene (rs4309, rs4362) were genotyped in 659 patients with SSc and 511 matched healthy controls. Among the whole SSc population, 453 (67%) patients with SSc had the limited cutaneous subtype, 47 (7%) had precapillary pulmonary arterial hypertension, 209 (32%) had digital ulcers, and 10 (1.5%) had renal crisis. A combined analysis of the available results for ACE I/D genotypes in Caucasians was also performed. RESULTS: There was no association between the 3 polymorphic markers and SSc for allelic and genotype frequencies. No association was observed for the different vascular subsets of the disease. Haplotype analyses did not detect any association. The lack of association for ACE I/D was confirmed by the combined analysis. CONCLUSION: These results in a large cohort of European Caucasian patients with SSc do not support that the ACE gene is implicated in the pathogenesis of SSc and its vascular damage.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".