The effect of childhood cow's milk intake and HLA-DR genotype on risk of islet autoimmunity and type 1 diabetes: The Diabetes Autoimmunity Study in the Young
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Bibliographic record
Abstract
BACKGROUND: Cow's milk intake has been inconsistently associated with islet autoimmunity (IA) and type 1 diabetes (T1D) development. Genetic and environmental factors may modify the effect of cow's milk on IA and T1D risk. METHODS: The Diabetes Autoimmunity Study in the Young (DAISY) follows children at increased T1D risk of IA (presence of autoantibodies to insulin, GAD65, or IA-2 twice in succession) and T1D development. We examined 1835 DAISY children with data on cow's milk intake: 143 developed IA, 40 subsequently developed T1D. Cow's milk protein and lactose intake were calculated from prospectively collected parent- and self-reported food frequency questionnaires (FFQ). High risk HLA-DR genotype: HLA-DR3/4,DQB1*0302; low/moderate risk: all other genotypes. We examined interactions between cow's milk intake, age at cow's milk introduction, and HLA-DR genotype in IA and T1D development. Interaction models contained the base terms (e.g., cow's milk protein and HLA-DR genotype) and an interaction term (e.g., cow's milk protein*HLA-DR genotype). RESULTS: In survival models adjusted for total calories, FFQ type, T1D family history, and ethnicity, greater cow's milk protein intake was associated with increased IA risk in children with low/moderate risk HLA-DR genotypes [hazard ratio (HR): 1.41, 95% confidence interval (CI): 1.08-1.84], but not in children with high risk HLA-DR genotypes. Cow's milk protein intake was associated with progression to T1D (HR: 1.59, CI: 1.13-2.25) in children with IA. CONCLUSIONS: Greater cow's milk intake may increase risk of IA and progression to T1D. Early in the T1D disease process, cow's milk intake may be more influential in children with low/moderate genetic T1D risk.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it