Exome Sequencing of Chinese Patients With Anticitrullinated Protein Antibody–Positive Rheumatoid Arthritis in Singapore
Bibliographic record
Abstract
Objective More than 130 susceptibility loci for rheumatoid arthritis (RA) have been identified with genome-wide association studies. To investigate the genetic predisposition of Chinese patients to anticitrullinated protein antibody (ACPA)-positive RA, we carried out an exome sequencing study. Methods Patients were recruited from 3 major public hospitals in Singapore: Tan Tock Seng Hospital (TTSH), Singapore General Hospital, and the National University Hospital. Controls came from an established exome collection and from the TTSH Health Control Biobank. All the participants were of Chinese descent. We performed whole-exome sequencing (WES) in 595 ACPA-positive patients with RA and 1281 controls and validated the candidate variants by genotyping 795 RA cases and 600 controls. Results The discovery cohort yielded 73 susceptibility single-nucleotide variants (SNVs) that reached statistical significance. In the validation study with an independent cohort, 2 SNVs remained significant:PCNXL4(P= 1.50 × 10–5) andDHRS7(P= 6.02 × 10–5). The majority of known susceptibility foci were not captured by exome sequencing. Conclusion In this WES study of ACPA-positive RA in Chinese patients, we discovered 2 new variants inPCNXL4andDHRS7associated with risk for RA.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".