Metabolic Dysfunction Associated With Alterations in Gut Microbiota in Adolescents With Obesity
Bibliographic record
Abstract
Obesity in childhood is associated with adulthood obesity, type 2 diabetes (T2D), and future metabolic complications. The gut microbiota is a modifier of host metabolic function with altered bacterial composition associated with disease risk. Few studies have investigated the relationships among metabolic disease, inflammation, and the gut microbiota in youth, in whom these connections likely originate. Here, we characterized the gut microbiome of a cohort of 56 adolescents with obesity and without diabetes using fecal DNA sequencing with absolute bacterial quantitation together with immune and metabolic profiling. We observed multi-log order variation in absolute bacterial biomass dependent on host environment and associated with bacterial taxonomic composition based on a nested case-control comparison. Participants with higher biomass displayed a healthier phenotype with higher gut microbiome diversity; lower abundance of taxa associated with inflammation and pathogenicity, such as Escherichia coli; and lower levels of neutrophil activities. Further association analysis revealed sex-dependent variation, with higher levels of insulin resistance, fasting triglycerides, and markers of neutrophil activities in male adolescents with lower bacterial biomass. Together, these results suggest that intestinal bacterial biomass and composition are associated with metabolic and inflammatory dysregulation evident before T2D diagnosis and identify sex differences in microbiome-associated metabolic dysfunction in adolescents with obesity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".