Association between cytokine gene polymorphisms and outcomes in renal transplantation: a meta-analysis of individual patient data
Bibliographic record
Abstract
BACKGROUND: Cytokine gene polymorphisms have been associated with poor outcomes after renal transplantation such as chronic allograft nephropathy (CAN), graft rejection (GR) and graft failure (GF), but the effects of these polymorphisms are still controversial. We therefore conducted a systematic review, with individual patient data (IPD) where possible, to determine the association between cytokine polymorphisms (TGF-beta1, TNF-alpha and IL-10) and outcomes after renal transplantation. METHODS: Five investigators were willing to participate and provided IPD. The outcomes of interest were GF, GR and CAN. Subjects with at least one of these were classified as having poor outcomes. Heterogeneity of gene effects was assessed. Multiple logistic regression was applied to assess gene effects, adjusting for clinical variables such as HLA matching and age. RESULTS: One-thousand and eighty-seven subjects were included in the IPD meta-analysis. Pooled results showed no evidence of heterogeneity and indicated that the strongest variables determining poor outcomes are HLA mismatching (OR = 1.6-1.8 for >/=3 HLA-A, -B, -DR mismatches compared with those with <3 mismatches) and age (OR = 1.2-1.4 for age 45 years or more). Incremental information on risk of a poor outcome is provided by the TGF-beta1c10 polymorphism (OR = 1.5, P = 0.034, 95% CI: 1.0-2.2 for TC genotype compared to TT genotype). Haplotypes of TGF-beta1 at c10 and c25 were inferred and the C-C haplotype was a marker of a poor outcome (OR = 1.3, P = 0.177, 95% CI: 1.0-2.3). Three polymorphisms of the IL-10 gene at -1082, -819, -592 are in strong linkage disequilibrium with each other (correlation coefficients: 0.6-1) and inferred haplotypes between these three loci show some association, with ACC increasing the risk of poor events compared to GCC (OR = 1.3, P = 0.044, 95% CI: 0.9-1.6). CONCLUSION: Pooled results to date suggest possible association between both the TGF-beta1 c10 polymorphism and a 3-SNP-haplotype of IL-10 and poor outcomes in renal transplantation, but this needs to be confirmed in larger studies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".