Genetic Risk Factors for Kidney Disease in Type 1 Diabetes
Bibliographic record
Abstract
Background: The genetic risk factors underlying kidney disease in type 1 diabetes (T1D) remain poorly understood. We examined whether previously-established genetic risk scores (GRS) for eGFR and albuminuria from general population cohorts correlate with these measures in adults with T1D beyond established demographic and clinical risk factors in the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study. Methods: We applied eGFR and albuminuria GRS derived previously in general population cohorts to 1,304 DCCT/EDIC participants with available genome-wide genotyping. Associations of eGFR GRS with continuous eGFR and of albuminuria GRS with continuous albumin excretion rate (AER) were assessed using linear regression models. Associations of eGFR GRS with incident eGFR <60 ml/min/1.73m2 and of albuminuria GRS with sustained AER > 30mg/24h and AER > 300 mg/24h were assessed using Cox proportional hazards models. Models were adjusted for age, sex, hemoglobin A1c, diabetes duration, systolic blood pressure, triglycerides, and beta-blocker use. Results: Overall, participants had a mean age of 60 years and 53% were male. 49% of participants were randomized to intensive versus conventional glucose-lowering therapy in the DCCT. Participants were followed for a median (IQR) 35 (33, 37) years. eGFR GRS was significantly associated with continuous eGFR (2.7+0.3 ml/min/1.73m2 higher eGFR per 1 SD higher GRS; p<0.0001) and incident eGFR <60 ml/min/1.73m2 (HR=0.83 [95% CI 0.74, 0.93] per 1 SD higher GRS; p=0.001). Albuminuria GRS was significantly associated with incident AER >30mg/24h (HR=1.12 [95% CI 1.03, 1.23] per 1 SD higher GRS; p=0.01), but not incident AER >300mg/24h or continuous AER. Associations were similar in analyses stratified by the original DCCT treatment group assignment (intensive versus conventional insulin therapy). Conclusion: Genetic factors that predict eGFR and albuminuria in the general population are similarly associated with these measures in adults with T1D after adjusting for demographic and diabetes-related clinical risk factors, including glycemic exposure as measured by hemoglobin A1c and by the original DCCT randomization to intensive versus conventional insulin therapy. Funding: NIDDK Support
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".