The association of previously reported polymorphisms for microvascular complications in a meta-analysis of diabetic retinopathy
Bibliographic record
Abstract
We investigated the association of signals from previous GWAS and candidate gene meta-analyses for diabetic retinopathy (DR) or nephropathy (DN), as well as an EPO variant in meta-analyses of severe (SDR) and mild diabetic retinopathy (MDR). Meta-analyses of SDR (≥severe non-proliferative diabetic retinopathy (NPDR) or history of panretinal photocoagulation) and MDR (≥mild NPDR), defined based on seven-field stereoscopic fundus photographs, were performed in two well-characterized type 1 diabetes (T1D) cohorts: the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC, n = 1,304) and Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR, n = 603). Among 34 previous signals for DR, after controlling for multiple testing, no association was replicated in our meta-analyses. rs1571942 and rs12219125 at PLXDC2 locus showed nominally significant (<0.05) association with SDR in the same direction as previous report, as did rs1801282 in PPARG gene with MDR. Among 55 loci previously associated with DN, three showed suggestive associations with SDR in our study without maintaining significance after correction for multiple testing. Of particular interest, rs1617640 (EPO) was not significantly associated with DR status, combined SDR-DN phenotype, time to SDR or time to DN (all P > 0.05). Lack of replication of previous DR hits and EPO despite reasonable statistical power implies that many of these may be false positives. Consistent with pleiotropy, we provide suggestive collective evidence for association between DR and variants previously associated with DN without reaching statistical significance at any single locus.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.029 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".