Exome-Wide Analysis Identifies a Rare EXD3 Missense Variant Associated With Diabetic Kidney Disease
Bibliographic record
Abstract
Introduction: Diabetic kidney disease (DKD) is a major complication of diabetes, with genetic factors contributing to its progression. Although genome-wide association studies (GWAS) have identified common variants, the role of low-frequency and rare coding variants remains underexplored. Methods: We performed exome-wide meta-analysis of up to 10,312 individuals with type 1 diabetes (T1D) genotyped using genome arrays with focused exome content. We included 10 DKD definitions based on albuminuria, estimated glomerular filtration rate (eGFR), or both. We analyzed nonsynonymous variants individually and used gene-level analyses for low-frequency (minor allele frequency [MAF] < 5%) and rare (< 1%) variants. Replication was performed in 10,066 participants with T1D and in UK Biobank participants with type 2 diabetes (T2D). Gene expression was assessed in cultured human podocytes. Results: = 0.014). Conclusion: in podocyte integrity and DKD pathogenesis. However, further functional investigations are necessary to understand the underlying molecular mechanisms.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".