Obese Adolescents With PCOS Have Altered Biodiversity and Relative Abundance in Gastrointestinal Microbiota
Bibliographic record
Abstract
CONTEXT: Alterations in gut microbiota relate to the metabolic syndrome, but have not been examined in at-risk obese youth with polycystic ovary syndrome (PCOS). OBJECTIVE: Compare the composition and diversity of the gut microbiota and associations with metabolic and hormonal measures between 2 groups of female adolescents with equal obesity with or without PCOS. DESIGN: Prospective, case-control cross-sectional study. SETTING: Tertiary-care center. PARTICIPANTS: A total of 58 obese female adolescents (n = 37 with PCOS; 16.1 ± 0.3 years of age; body mass index [BMI] 98.5th percentile) and (n = 21 without PCOS; 14.5 ± 0.4 years of age; BMI 98.7th percentile). OUTCOMES: Bacterial diversity, percent relative abundance (%RA), and correlations with hormonal and metabolic measures. RESULTS: Participants with PCOS had decreased α-diversity compared with the non-PCOS group (Shannon diversity P = 0.045 and evenness P = 0.0052). β-diversity, reflecting overall microbial composition, differed between groups (P < 0.001). PCOS had higher %RA of phyla Actinobacteria (P = 0.027), lower Bacteroidetes (P = 0.004), and similar Firmicutes and Proteobacteria. PCOS had lower %RA of families Bacteroidaceae (P < 0.001) and Porphyromonadaceae (P = 0.024) and higher Streptococcaceae (P = 0.047). Lower bacterial α-diversity was strongly associated with higher testosterone concentrations. Several individual taxa correlated with testosterone and metabolic measures within PCOS and across the entire cohort. Receiver operative curve analysis showed 6 taxa for which the %RA related to PCOS status and lower Bacteroidaceae conferred a 4.4-fold likelihood ratio for PCOS. CONCLUSION: Alterations in the gut microbiota exist in obese adolescents with PCOS versus obese adolescents without PCOS and these changes relate to markers of metabolic disease and testosterone. Further work is needed to determine if microbiota changes are reflective of, or influencing, hormonal metabolism.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".