Androgen receptor gene exon 1 CAG repeat polymorphism in Finnish patients with childhood-onset type 1 diabetes
Bibliographic record
Abstract
OBJECTIVE: Animal models suggest that androgen receptor gene polymorphisms might affect disease predisposition in human immune-mediated diabetes. The aim of this study was to investigate the effect of the human androgen receptor gene exon 1 CAG repeat polymorphisms on type 1 diabetes (T1D) susceptibility. DESIGN AND METHODS: A combined strategy of case-control and family-based approaches was used. Affected sibling pair families (n=120), nuclear families (n=645) and cohorts of sporadic cases (n=208) and controls (n=1381) were genotyped for androgen receptor gene exon 1 CAG repeat polymorphism. An automated fluorescence-based DNA fragment-sizing method was used. RESULTS: The distribution of CAG repeat alleles did not differ significantly between patients and controls. However, short repeat alleles (7-14) were more prevalent among cases in girls compared with controls (8.77% vs 5.91%; P=0.03). Long repeat alleles (19-28) were less frequent among HLA DR3-positive diseased boys than in DR3-positive control boys (32.6% vs 40.6%; P=0.011). The differences were not significant after adjustment for multiple comparisons. Transmission of CAG repeat alleles was not different from expected in the total material. However, transmissions to girls deviated from the expected value significantly (extended transmission disequilibrium test (ETDT) 37.82; P=0.0016). A decreased transmission of the alleles with 13, 20 and 26 repeats to girls was observed (T%0, P=0.046; T%25.5, P=0.0003, T%0, P=0.025). CONCLUSION: The results do not support a common role for the androgen receptor gene exon 1 CAG repeat in T1D susceptibility; however, an effect of a disease variant in linkage disequilibrium could be detected.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".