DNA repair in lupus
Bibliographic record
Abstract
The myriad of mouse genetic alterations that result in a lupus-like phenotype and the >100 genes now known to be involved in human lupus are all probably only a hint at the potential complexity of the many mechanisms that lead to systemic lupus erythematosus (SLE). We have applied exome sequencing to 24 SLE patients and their parents (trios) in an effort to conquer the data analysis and to identify candidate genes that may contribute when the activity of their gene products were substantially altered. The proband of one of our SLE trios had de novo mutations in RAD54B that was predicted to change ARG to GLN and to be severely damaging to protein product activity by multiple algorithms. A second much more conservative de novo mutation in DOCK8 was not predicted to be consequential. RAD54B is a component of the homologous recombination DNA repair pathway. Cells from the SLE proband were unusually sensitive to ionizing radiation by the colony survival and comet tail assays. Ionizing radiation selectively induced interferon responsive genes in cells from this patient and not from controls. Transfection of the wild-type gene into the cells from this patient led to overexpression of the RAD54B gene product and returned ionizing radiation resistance toward normal. These data in addition to the other five other genes directly or indirectly involved in altering risk of SLE by influencing DNA repair ( TREX1, RAD51B, XRCC1, XRCC3 , and XRCC4 ) implicate base excision repair, nonhomologous end joining, and homologous recombination. These results suggest that multiple DNA repair mechanisms contribute to SLE susceptibility.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".