In silico replication of the genome-wide association results of the Type 1 Diabetes Genetics Consortium
Bibliographic record
Abstract
Recently, the Type 1 Diabetes Genetics Consortium (T1DGC) reported 22 novel type 1 diabetes (T1D)-associated loci identified by meta-analysis of three genome-wide association studies (GWASs) with a case-control design. However, the association of 10 of these 22 reported loci was not confirmed in the T1DGC family cohort (P > 0.1). To address concerns about potential bias from population stratification, this study aims to replicate the association in three independent GWAS cohorts, one of which was based on the stratification-proof transmission disequilibrium analysis. Three European-descent population samples were included in this study: 483 cases and both parents, a case-control cohort of 514 cases and 2027 controls, and an additional cohort of 1078 cases and 341 controls from the dbGaP database. Among the 22 SNPs reported by the T1DGC, we had high-quality genotypes for 15; the remaining were imputed. T1D association was replicated in seven loci after Bonferroni correction for 22 independent hypotheses. An additional eight loci had nominal (one-sided) significance of P < 0.1 in the same direction, giving a false discovery rate of 3.35%. The genetic susceptibility conferred by non-HLA loci in our family cohort with one affected offspring was higher than the T1DGC multiplex families. Reciprocally, the frequency of strongly predisposing HLA alleles in the multiplex families was higher. This study replicated T1D association with at least as many of these novel loci as expected from the power of our sample size, thus supporting the validity of the new discoveries.
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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 | 0.042 | 0.078 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".