Infections in the first year of life and development of beta cell autoimmunity and clinical type 1 diabetes in high-risk individuals: the TRIGR cohort
Bibliographic record
Abstract
AIMS/HYPOTHESIS: Accumulated data suggest that infections in early life contribute to the development of type 1 diabetes. Using data from the Trial to Reduce IDDM in the Genetically at Risk (TRIGR), we set out to assess whether children who later developed diabetes-related autoantibodies and/or clinical type 1 diabetes had different exposure to infections early in life compared with those who did not. METHODS: A cohort of 2159 children with an affected first-degree relative and HLA-conferred susceptibility to type 1 diabetes were recruited between 2002 and 2007 and followed until 2017. Infections were registered prospectively. The relationship between infections in the first year of life and the development of autoantibodies or clinical type 1 diabetes was analysed using univariable and multivariable Cox regression models. As this study was exploratory, no adjustment was made for multiple comparisons. RESULTS: Adjusting for HLA, sex, breastfeeding duration and birth order, those who had seven or more infections during their first year of life were more likely to develop at least one positive type 1 diabetes-related autoantibody (p=0.028, HR 9.166 [95% CI 1.277, 65.81]) compared with those who had no infections. Those who had their first viral infection aged between 6 and 12 months were less likely to develop at least one positive type 1 diabetes-related antibody (p=0.043, HR 0.828 [95% CI 0.690, 0.994]) or multiple antibodies (p=0.0351, HR 0.664 [95% CI 0.453, 0.972]). Those who had ever had an unspecified bacterial infection were more likely to develop at least one positive type 1 diabetes-related autoantibody (p=0.013, HR 1.412 [95% CI 1.075, 1.854]), to develop multiple antibodies (p=0.037, HR 1.652 [95% CI 1.030, 2.649]) and to develop clinical type 1 diabetes (p=0.011, HR 2.066 [95% CI 1.182, 3.613]). CONCLUSIONS/INTERPRETATION: We found weak support for the assumption that viral infections early in life may initiate the autoimmune process or later development of type 1 diabetes. In contrast, certain bacterial infections appeared to increase the risk of both multiple autoantibodies and clinical type 1 diabetes.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".