High-activity Classical and Alternative Complement Pathway Genotypes—Association With Donor-specific Antibody-triggered Injury and Renal Allograft Survival
Bibliographic record
Abstract
Background. Complement may contribute to donor-specific antibody (DSA)-triggered transplant injury. Here, we investigated whether the intrinsic strength of classical pathway and alternative pathway (AP) relates to the pathogenicity of DSA. Methods. Classical pathway and AP high-activity genotypes were defined according to C4 gene copy number and the presence of functional polymorphisms in C3 (C3102G), factor B (fB32R), and factor H (fH62V) genes. Associations of these genotypes with blood complement profiles and morphologic/molecular rejection features were evaluated in a cohort of 83 DSA-positive patients (antibody-mediated rejection [AMR], n = 47) identified upon cross-sectional screening of 741 kidney allograft recipients ≥180 days posttransplantation. Associations with long-term graft survival were evaluated in a larger kidney transplant cohort (n = 660) not enriched for a specific type of rejection. Results. In the cohort of DSA-positive subjects, the number of C4 gene copies was related to C4 protein levels in serum and capillary C4d staining, but not AMR activity. Patients with a high-activity AP complotype, which was associated with complement consumption in serum, showed enhanced microcirculation inflammation (median glomerulitis plus peritubular capillaritis score, 2 [interquartile range, 0–4 versus 1 0–2]; P = 0.037). In the larger transplant cohort, this complotype was associated with a slightly increased risk of graft loss (hazard ratio, 1.52; 95% confidence interval, 1.02-2.25; P = 0.038 and multivariable Cox model, 1.55; 1.04-2.32; P = 0.031). Conclusions. Our study suggests a contribution of complement genetics to the phenotypic presentation of AMR. Future studies will have to clarify whether a possible association of AP strength with graft survival relates to enhanced antibody-triggered injury.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".