Association study of<i>interleukin-19 rs2243188</i>polymorphism with systemic lupus erythematosus in a Chinese population
Bibliographic record
Abstract
The purpose of this study was to evaluate whether a single-nucleotide polymorphism (SNP), rs2243188 of interleukin-19 (IL-19), show significant evidence for association with SLE in a Chinese population. A total of 545 SLE patients and 613 healthy controls were collected in the present study. The genotyping of IL-19 rs2243188 polymorphism was detected by TaqMan allele discrimination assay on the 7300 real time polymorphism chain reaction system. The minor C allele of rs2243188, relative to the major A allele, appeared to have a significantly lower frequency in SLE patients (31.0%) as compared with controls (35.5%) (χ(2) = 5.19, p = 0.023). We also discovered a statistical significance in the dominant model (CC + CA versus AA: OR = 0.755, 95% CI = 0.598-0.953, p = 0.018). However, no significant difference in genotype distribution was found between SLE patients and controls (p = 0.056). Furthermore, an increased frequency of CC genotype were also detected in lupus nephritis (LN) groups as compared with non-LN groups (p = 0.024). Besides, the individuals with CC genotype had a 2.201-fold higher risk for the susceptibility to LN than those A allele carriers (AA + CA) (p = 0.006). Unfortunately, the analyses on the relationship of IL-19 rs2243188 with several clinical manifestations of SLE failed to find any significant results. In conclusion, our observations suggested the minor C allele of SNP rs2243188 might be a protective factor for SLE in a Chinese Han population. Moreover, the subgroup analysis highlighted that IL-19 rs2243188 SNP was associated with the susceptibility to LN patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".