Identification of novel susceptibility genes in childhood‐onset systemic lupus erythematosus using a uniquely designed candidate gene pathway platform
Bibliographic record
Abstract
OBJECTIVE: Childhood-onset systemic lupus erythematosus (SLE) presents a unique subgroup of patients for genetic study. The present study was undertaken to identify susceptibility genes contributing to SLE, using a novel candidate gene pathway microarray platform to investigate gene expression in patients with childhood-onset SLE and both of their parents. METHODS: Utilizing bioinformatic tools, a platform of 9,412 single-nucleotide polymorphisms (SNPs) from 1,204 genes was designed and validated. Molecular inversion probes and high-throughput SNP technologies were used for assay development. Seven hundred fifty three subjects, corresponding to 251 full trios of childhood-onset SLE families, were genotyped and analyzed using transmission disequilibrium testing (TDT) and multitest corrections. RESULTS: Family-based TDT showed a significant association of SLE with a N673S polymorphism in the P-selectin gene (SELP) (P = 5.74 x 10(-6)) and a C203S polymorphism in the interleukin-1 receptor-associated kinase 1 gene (IRAK1) (P = 9.58 x 10(-6)). These 2 SNPs had a false discovery rate for multitest correction of <0.05, and therefore a >95% probability of being considered as proven. Furthermore, 7 additional SNPs showed q values of <0.5, suggesting association with SLE and providing a direction for followup studies. These additional genes notably included TNFRSF6 (Fas) and IRF5, supporting previous findings of their association with SLE pathogenesis. CONCLUSION: SELP and IRAK1 were identified as novel SLE-associated genes with a high degree of significance, suggesting new directions in understanding the pathogenesis of SLE. The overall design and results of this study demonstrate that the candidate gene pathway microarray platform used provides a novel and powerful approach that is generally applicable in identifying genetic foundations of complex diseases.
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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 | 0.004 | 0.000 |
| 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 | 0.000 |
| 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".