Virus induced dysbiosis promotes type 1 diabetes onset
Bibliographic record
Abstract
Autoimmune disorders are complex diseases of unclear etiology, although evidence suggests that the convergence of genetic susceptibility and environmental factors are critical. In type 1 diabetes (T1D), enterovirus infection and disruption of the intestinal microbiota are two environmental factors that have been independently associated with T1D onset in both humans and animal models. However, the possible interaction between viral infection and the intestinal microbiota remains unknown. Here, we demonstrate that Coxsackievirus B4 (CVB4), an enterovirus that accelerates T1D onset in non-obese diabetic (NOD) mice, induced restructuring of the intestinal microbiome prior to T1D onset. Microbiome restructuring was associated with an eroded mucosal barrier, bacterial translocation to the pancreatic lymph node, and increased circulating and intestinal commensal-reactive antibodies. The CVB4-induced change in community composition was strikingly similar to that of uninfected NOD mice that spontaneously developed diabetes, implying a mutual “diabetogenic” microbiome. Notably, members of the Bifidobacteria and Akkermansia genera emerged as conspicuous members of this diabetogenic microbiome, implicating these taxa, among others, in diabetes onset. Further, fecal microbiome transfer (FMT) of the diabetogenic microbiota from CVB4-infected mice enhanced T1D susceptibility and led to diminished expression of the short chain fatty acid receptor GPR43 and fewer IL-10-expressing regulatory CD4+ T cells in the intestine of naïve NOD recipients. These findings support an overlap in known environmental risk factors of T1D, and suggest that microbiome disruption and impaired intestinal homeostasis contribute to CVB-enhanced autoreactivity and T1D.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".