High‐density genotyping of STAT4 reveals multiple haplotypic associations with systemic lupus erythematosus in different racial groups
Bibliographic record
Abstract
OBJECTIVE: Systemic lupus erythematosus (SLE) is the prototypical systemic autoimmune disorder, with complex etiology and a strong genetic component. Recently, gene products involved in the interferon pathway have been under intense investigation in terms of the pathogenesis of SLE. STAT-1 and STAT-4 are transcription factors that play key roles in the interferon and Th1 signaling pathways, making them attractive candidates for involvement in SLE susceptibility. METHODS: Fifty-six single-nucleotide polymorphisms (SNPs) across STAT1 and STAT4 on chromosome 2 were genotyped using the Illumina platform, as part of an extensive association study in a large collection of 9,923 lupus patients and control subjects from different racial groups. DNA samples were obtained from the peripheral blood of patients with SLE and control subjects. Principal components analyses and population-based case-control association analyses were performed, and the P values, false discovery rate q values, and odds ratios with 95% confidence intervals were calculated. RESULTS: We observed strong genetic associations with SLE and multiple SNPs located within STAT4 in different ethnic groups (Fisher's combined P = 7.02 x 10(-25)). In addition to strongly confirming the previously reported association in the third intronic region of this gene, we identified additional haplotypic association across STAT4 and, in particular, a common risk haplotype that is found in multiple racial groups. In contrast, only a relatively weak suggestive association was observed with STAT1, probably due to its proximity to STAT4. CONCLUSION: Our findings indicate that STAT4 is likely to be a crucial component in SLE pathogenesis in multiple racial groups. Knowledge of the functional effects of this association, when they are revealed, might improve our understanding of the disease and provide new therapeutic targets.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".