The Autoimmune Disease Risk Allele of UBE2L3 in African American Patients with Systemic Lupus Erythematosus: A Recessive Effect Upon Subphenotypes
Bibliographic record
Abstract
OBJECTIVE: UBE2L3 is associated with susceptibility to systemic lupus erythematosus (SLE) and rheumatoid arthritis in European ancestry populations, and this locus has not been investigated fully in non-European populations. We studied the UBE2L3 risk allele for association with SLE, interferon-α (IFN-α), and autoantibodies in a predominantly African American SLE cohort. METHODS: We studied 395 patients with SLE and 344 controls. The UBE2L3 rs5754217 polymorphism was genotyped using Taqman primer-probe sets, and IFN-α was measured using a reporter cell assay. RESULTS: The UBE2L3 rs5754217 T allele was strongly enriched in African American patients with anti-La antibodies as compared to controls, and a recessive model was the best fit for this association (OR 2.55, p = 0.0061). Serum IFN-α also demonstrated a recessive association with the rs5754217 genotype in African American patients, and the TT/anti-La-positive patients formed a significantly high IFN-α subgroup (p = 0.0040). Similar nonstatistically significant patterns of association were observed in the European American patients with SLE. Case-control analysis did not show large allele frequency differences, supporting the idea that this allele is most strongly associated with anti-La-positive patients. CONCLUSION: This pattern of recessive influence within a subgroup of patients may explain why this allele does not produce a strong signal in standard case-control studies, and subphenotypes should be included in future studies of UBE2L3. The interaction we observed between UBE2L3 genotype and autoantibodies upon serum IFN-α suggests a biological role for this locus in patients with SLE in vivo.
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) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".