A T-cell intrinsic Role for <i>APOL1</i> Risk Alleles in Allograft Rejection
Bibliographic record
Abstract
Abstract African Americans have an increased risk of kidney disease due to exonic variants in Apolipoprotein-L1 (G1 and G2). These prevalent variants have also been linked with kidney rejection, but outside of association with African ancestry, underpinning causal mechanisms are unknown. We investigated T-cell function using transgenic mice with physiologic expression of wild type (G0-), G1-, or G2-APOL1. Mice with variant APOL1 showed greater CD8+T-cell activation with expansion of a central memory (TCM) subset. Stimulated G1-CD8+T-cells showed enhanced proliferation and cytokine production, which reversed with APOL1 inhibition. In MHC-mismatched cardiac transplants, G1-mice demonstrated greater CD8+T-cell infiltration and reduced survival. Bulk transcriptome of G1-CD8+T-cells, and single-cell transcriptome of graft infiltrating TCMs, showed enrichment of canonical T-cell receptor (TCR) pathways including Ca 2+ -signaling. G1-CD8+T-cells demonstrated baseline ER-Ca 2+ depletion followed by sustained increases in cytosolic-Ca 2+ upon TCR stimulation. G1-CD8+T-cells were more sensitive to Ca 2+ chelation, or store-operated Ca 2+ entry inhibition, and relatively resistant to calcineurin antagonism vs. G0-CD8+T-cells. Analogously, in a kidney transplant cohort, APOL1-variant recipients developed rejection when they had elevated peripheral TCMs before transplantation and despite significantly higher tacrolimus levels vs G0/G0-AAs with rejection. In summary, we unravel an excitatory T-cell intrinsic mechanism for APOL1 exonic variants, causally linking them with kidney rejection.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".