HLA-D and PLA2R1 risk alleles associate with recurrent primary membranous nephropathy in kidney transplant recipients
Bibliographic record
Abstract
Recurrence of primary membranous nephropathy after transplantation occurs in up to 44% of patients and is driven by PLA2R antibody. Here, we asked whether genetic determinants could improve risk prediction. First, we sequenced PLA2R1 and HLA-D loci in 248 patients with primary membranous nephropathy and identified two independent single nucleotide polymorphisms (SNPs) at risk for primary membranous nephropathy at each locus. These were rs9271188 (intergenic between HLA-DRB1 and HLA-DQA1,) and rs9275086 (intergenic between HLA-DQB1 and HLA-DQA2) at the HLA-D locus along with rs6726925 and rs13018963 at the PLA2R1 locus. Then we investigated whether primary membranous nephropathy at-risk variants were associated with recurrence in a retrospective cohort of 105 donor-recipient pairs and a replication cohort of 40 pairs. Seven SNPs located between HLA-DRB1 and HLA-DQA1 in linkage disequilibrium with rs9271188, and three SNPs in the PLA2R1 region predicted recurrence when presented by the donor, but not when presented by the recipient. The two SNPs in the HLA-D region most strongly associated with recurrence (rs9271705 and rs9271550) were confirmed in the replication cohort. A genetic risk score based on the two best predictors at each locus (rs9271705, rs9271550, rs17830558, and rs3828323) identified a group of patients with high risk of recurrence. Thus, our results suggest that the graft contributes to recurrence of primary membranous nephropathy through the disease susceptibility HLA-D and PLA2R1 SNPs in an autoimmune milieu. Further studies are needed before implementation of genetic testing for these in donor selection.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".