Interleukin 6 Gene Polymorphisms Are Associated with Systemic Lupus Erythematosus in Koreans
Bibliographic record
Abstract
OBJECTIVE: Interleukin 6 (IL-6) gene polymorphisms are known to play a role in chronic inflammatory disorders. We searched for polymorphisms in the IL-6 gene and described their pathogenic role in Korean patients with systemic lupus erythematosus (SLE). METHODS: Genomic DNA was extracted from 151 patients with SLE and 151 controls, and about 1.4 kb-sized IL-6 genes located between promoter region and exon 2 region were amplified by polymerase chain reaction. The promoter activity was analyzed by luciferase reporter assay in Hep3B cells and HeLa cells. RESULTS: We identified 4 single-nucleotide polymorphisms (SNP; -572 C > G, -278 A > C in the promoter, and 330 T > G, and 334 A > T in exon 2) and a -373 A(n)T(n) tract polymorphism in the IL-6 gene. The genotype frequency, -373 A(10)T(11), -278 C, and 334 T allele were significantly associated with SLE (p < 0.001, p = 0.03 and p = 0.005, respectively). Patients with SLE carrying the -572 G allele had anti-dsDNA more frequently (p = 0.007). In addition, thrombocytopenia was significantly more common in patients carrying the -278 C allele (p = 0.006). In the haplotype analysis, patients with SLE had more frequently haplotype HT3 (CA(10)T(11)ATA, dominant model, p = 0.012) that was associated with arthritis, leukopenia, anti-dsDNA, and hypocomplementemia. Promoter reporter structures carrying the -278 C allele displayed significantly higher promoter activity than the -278 A allele in Hep3B cells (p < 0.001) and HeLa cells (p < 0.001). CONCLUSION: These data suggest that IL-6 gene polymorphisms are associated with disease susceptibility and phenotype of SLE. In addition, promoter polymorphisms may be involved in regulation of IL-6 expression.
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 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 | 0.000 | 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) | 0.002 | 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".