Subphenotype mapping in systemic lupus erythematosus identifies multiple novel loci associated with circulating interferon alpha
Bibliographic record
Abstract
Systemic lupus erythematosus (SLE) is a chronic autoimmune disorder characterized by inflammation of multiple organ systems, loss of tolerance to self-antigens, and dysregulated interferon responses. SLE is both genetically and phenotypically heterogeneous, and we hypothesize that this greatly reduces the power of overall case-control studies in SLE. Increased circulating level of the cytokine interferon alpha (IFNα) is a stable, heritable trait in SLE which has been implicated in primary disease pathogenesis. Forty to 50% of patients have high IFNα, and high levels correspond with clinical differences. To study genetic heterogeneity in SLE, we performed a case-case study comparing patients with high versus low IFNα in over 1,800 SLE cases. Four hundred European ancestry cases formed the discovery GWAS set, and 1,443 cases from a large independent multi-ancestral replication cohort were used to validate associations. In meta-analysis, the top associations in European ancestry were PRKG1 rs7897633 ( P Meta = 2.75 × 10 ) and PNP rs1049564 (P Meta = 1.24 × 10 ). We also found evidence for cross-ancestral background associations with the ANKRD44 and PLEKHF2 loci. These loci have not been previously identified in case-control SLE genetics studies. Bioinformatic analyses implicate these loci functionally in dendritic cells and natural killer cells, both of which are involved in IFNα production in SLE. As case-control studies of complex heterogeneous diseases reach a limit of feasibility with respect to subject number and detectable effect size, the study of informative pathogenic subphenotypes becomes a highly attractive and efficient strategy for genetic discovery in complex human disease.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".