Autoantibodies to LG3 are associated with poor long‐term survival after liver retransplantation
Bibliographic record
Abstract
Autoantibodies are detrimental to the survival of organ transplantation. We demonstrated that Angiotensin II Type I Receptor agonistic autoantibodies (AT1R-AA) were associated with poor outcomes after liver retransplantation. To examine the effect of other autoantibodies, we studied a retrospective cohort of 93 patients who received a second liver transplant. Pre-retransplant sera were tested with Luminex-based solid-phase assays. Among 33 tested autoantibodies, 15 were significantly higher in 48 patients who lost their regrafts than 45 patients whose regrafts were still functioning. Specifically, patients with autoantibodies to the C-terminal laminin-like globular domain of Perlecan (LG3) experienced significantly worse regraft survival (p = .002) than those with negative LG3 autoantibodies (LG3-A). In multivariate analysis, LG3-A (HR = 2.35 [1.11-4.98], p = .027) and AT1R-AA (HR = 2.09 [1.07-4.10], p = .032) remained significant predictors of regraft loss after adjusting for recipient age and sex. There were synergistic deleterious effects on regraft survival in patients who were double-positive for LG3-A and donor-specific antibody (DSA) (HR = 5.26 [2.15-12.88], p = .001), or LG3-A and AT1R-AA (HR = 3.23 [1.37-7.66], p = .008). All six double-positive patients lost their liver regrafts. In conclusion, LG3-A is associated with inferior long-term outcomes of a second liver transplant. Screening anti-HLA antibodies and autoantibodies such as LG3-A/AT1R-AA identifies patients with a higher risk for liver transplantation.
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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) | 0.001 | 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".