Designing and implementing sample and data collection for an international genetics study: the Type 1 Diabetes Genetics Consortium (T1DGC)
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The Type 1 Diabetes Genetics Consortium (T1DGC) is an international project whose primary aims are to: (a) discover genes that modify type 1 diabetes risk; and (b) expand upon the existing genetic resources for type 1 diabetes research. The initial goal was to collect 2500 affected sibling pair (ASP) families worldwide. METHODS: T1DGC was organized into four regional networks (Asia-Pacific, Europe, North America, and the United Kingdom) and a Coordinating Center. A Steering Committee, with representatives from each network, the Coordinating Center, and the funding organizations, was responsible for T1DGC operations. The Coordinating Center, with regional network representatives, developed study documents and data systems. Each network established laboratories for: DNA extraction and cell line production; human leukocyte antigen genotyping; and autoantibody measurement. Samples were tracked from the point of collection, processed at network laboratories and stored for deposit at National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repositories. Phenotypic data were collected and entered into the study database maintained by the Coordinating Center. RESULTS: T1DGC achieved its original ASP recruitment goal. In response to research design changes, the T1DGC infrastructure also recruited trios, cases, and controls. Results of genetic analyses have identified many novel regions that affect susceptibility to type 1 diabetes. T1DGC created a resource of data and samples that is accessible to the research community. LIMITATIONS: Participation in T1DGC was declined by some countries due to study requirements for the processing of samples at network laboratories and/or final deposition of samples in NIDDK Central Repositories. Re-contact of participants was not included in informed consent templates, preventing collection of additional samples for functional studies. CONCLUSIONS: T1DGC implemented a distributed, regional network structure to reach ASP recruitment targets. The infrastructure proved robust and flexible enough to accommodate additional recruitment. T1DGC has established significant resources that provide a basis for future discovery in the study of type 1 diabetes genetics.
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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 | 0.241 | 0.236 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.008 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.007 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".