Response to Intravenous Cyclophosphamide Treatment for Lupus Nephritis Associated with Polymorphisms in the<i>FCGR2B-FCRLA</i>Locus
Bibliographic record
Abstract
OBJECTIVE: Cyclophosphamide (CYC) is an immunosuppressant drug widely used to treat various diseases including lupus nephritis, but its efficacy highly varies from individual to individual. This pharmacogenomics association study searched for genetic variations associated with CYC efficacy. METHODS: Genome-wide association scan was performed for 109 Korean patients with systemic lupus erythematosus with lupus nephritis (classes III-V) who received intravenous CYC induction therapy. Genetic differences between responders and nonresponders were examined using Cochran-Armitage trend tests, and genotype imputation was used for defining the association locus. RESULTS: Genetic polymorphisms in the Fcγ receptor gene (FCGR) cluster at human chromosome 1q23, previously associated with lupus nephritis susceptibility, were associated with the response to CYC treatment for lupus nephritis. Significant response association was found for 3 perfectly correlated (r(2) = 1) single-nucleotide polymorphisms (SNP): rs6697139, rs10917686, and rs10917688, located between the FCGR2B and FCRLA genes (p = 3.4 × 10(-8)). Carriage of the minor alleles in these SNP was found only in nonresponders (31%) and none in responders (0%). CONCLUSION: This first genome-wide association approach for CYC response yielded a robust profile of genetic associations including large-effect SNP in the FCGR2B-FCRLA locus, which may provide better insights to CYC metabolism and efficacy.
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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) | 0.000 | 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) | 0.001 | 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".