Pilot Genome-Wide Association Search Identifies Potential Loci for Risk of Erectile Dysfunction in Type 1 Diabetes Using the DCCT/EDIC Study Cohort
Bibliographic record
Abstract
PURPOSE: We identified genetic predictors of diabetes associated erectile dysfunction using genome-wide and candidate gene approaches in a cohort of men with type 1 diabetes. MATERIALS AND METHODS: We examined 528 white men with type 1 diabetes, including 125 with erectile dysfunction, from DCCT (Diabetes Control and Complications Trial) and its observational followup, the EDIC (Epidemiology of Diabetes Interventions and Complications) study. Erectile dysfunction was identified from a single International Index of Erectile Function item. A Human1M BeadChip (Illumina®) was used for genotyping. A total of 867,125 single nucleotide polymorphisms were subjected to analysis. Whole genome and candidate gene approaches were used to test the hypothesis that genetic polymorphisms may predispose men with type 1 diabetes to erectile dysfunction. Univariate and multivariate models were used, controlling for age, HbA1c, diabetes duration and prior randomization to intensive or conventional insulin therapy during DCCT. A stratified false discovery rate was used to perform the candidate gene approach. RESULTS: Two single nucleotide polymorphisms located on chromosome 3 in 1 genomic loci were associated with erectile dysfunction with p <1 × 10(-6), including rs9810233 with p = 7 × 10(-7) and rs1920201 with p = 9 ×10(-7). The nearest gene to these 2 single nucleotide polymorphisms is ALCAM. Genetic association results at these loci were similar on univariate and multivariate analysis. No candidate genes met the criteria for statistical significance. CONCLUSIONS: Two single nucleotide polymorphisms, rs9810233 and rs1920101, which are 25 kb apart, are associated with erectile dysfunction, although they do not meet the standard genome-wide association study significance criterion of p <5 × 10(-8). Other studies with larger sample sizes are required to determine whether ALCAM represents a novel gene in the pathogenesis of diabetes associated erectile dysfunction.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".