PRKCB is associated with calcineurin inhibitor-induced renal dysfunction in heart transplant recipients
Bibliographic record
Abstract
OBJECTIVES: Single nucleotide polymorphisms (SNPs) in the transforming growth factor-β1 gene (TGFB1) have been inconsistently associated with calcineurin inhibitor (CNI)-induced renal dysfunction following cardiac transplantation. The impact of genetic variants related to the renin-angiotensin-aldosterone system (RAAS) and natriuretic peptides, which are implicated in CNI nephrotoxicity, is unknown. The primary objective of this study was to validate the association between two common variants in TGFB1 (rs1800470, rs1800471) and postcardiac transplant renal function. The secondary objective was to investigate the effect of candidate genes related to the RAAS, natriuretic peptides, and other elements involved in the intracellular signaling of these pathways. METHODS: We conducted a retrospective cohort study of 158 heart transplant recipients treated with CNIs, and evaluated the association between select SNPs and the estimated glomerular filtration rate as calculated by the Modification of Diet in Renal Disease simplified formula. A total of 273 SNPs distributed in 44 genes were tested. RESULTS: No association was observed between TGFB1 variants and renal function. One polymorphism in the protein kinase C-β gene (PRKCB; rs11074606), which is implicated in the RAAS intracellular signaling, was significantly associated with post-transplant estimated glomerular filtration rate after adjusting for possible confounders (P=0.00049). This marker is in linkage disequilibrium with two variants located in putative regulatory regions of the gene (rs2283541, rs1013316). CONCLUSION: Our results suggest that PRKCB may be a potential predictor of CNI-induced nephrotoxicity in heart transplant recipients, and could therefore be a promising candidate to identify patients who are most susceptible to this adverse drug reaction.
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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".