Evidence for Genetic Association of CARD9 and SNAPC4 with Ankylosing Spondylitis in a Chinese Han Population
Bibliographic record
Abstract
OBJECTIVE: A genome-wide association study and 2 replication studies identified 2 single-nucleotide polymorphisms (SNP) of caspase recruitment domain-containing protein 9 (CARD9) and small nuclear RNA-activating complex polypeptide 4 (SNAPC4) at Chr 9q34.3 associated with ankylosing spondylitis (AS) in whites. We explored a possible association of SNP in CARD9 and SNAPC4 and AS in a Chinese Han population from Shandong. METHODS: The study included 1150 patients with AS and 1120 healthy controls who underwent genotyping for 4 SNP of CARD9 and 2 of SNAPC4; we replicated the results in another 490 patients and 380 healthy controls of Ningxia Han Chinese during the same time. We used quantitative real-time PCR (qRT-PCR) to measure CARD9 and SNAPC4 mRNA expression in peripheral leukocytes from 44 patients and 36 controls and allele-specific mRNA expression of CARD9 and SNAPC4 in leukocytes from 130 controls. RESULTS: We validated that an SNP in SNAPC4, rs11145835, was significantly associated with AS in our Chinese Han population (p = 0.001) and replicated the association in samples from the Chinese Ningxia Han population (p = 0.002). Carrying the G allele of rs11145835 was associated with increased risk of AS (OR 1.34, 95% CI 1.12-1.59) and with decreased expression of CARD9 (p = 0.001) and SNAPC4 (p = 0.02) in leukocytes. SNAPC4 mRNA expression was lower in leukocytes from patients than from controls (p = 0.0002). CONCLUSION: Our study confirmed that an SNP rs11145835 in 9q34.3 that harbors CARD9 and SNAPC4 is associated with AS in a Chinese Han population, and rs11145835 in SNAPC4 is a potential causal variant.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".