Pangenomic analysis identifies correlations between <i>Akkermansia</i> species and subspecies and human health outcomes
Bibliographic record
Abstract
Aim: Akkermansia are common members of the human gastrointestinal microbiota. The prevalence of these mucophilic bacteria, especially Akkermansia muciniphila (A. muciniphila ), correlates with immunological and metabolic health. The genus Akkermansia in humans includes species with significantly larger genomes than A. muciniphila , leading us to postulate that this added genetic content may influence how they impact human metabolic and immunological health. Methods: We conducted a pangenomic analysis of 234 Akkermansia complete or near-complete genomes. We also used high-resolution species and subspecies assignments to reanalyze publicly available metagenomic datasets to determine if there are relationships between Akkermansia species and A. muciniphila clades with various disease outcomes. Results: Analysis of genome-wide average nucleotide identity, 16S rRNA gene identity, conservation of core Akkermansia genes, and analysis of the fatty acid composition of representative isolates support the partitioning of the genus Akkermansia into several species. In addition, A. muciniphila sensu stricto , the most prevalent Akkermansia species in humans, should be subdivided into two subspecies. For a pediatric cohort, we observed species-specific correlations between Akkermansia abundance with baseline obesity or after various interventions. For inflammatory bowel disease cohorts, we identified a decreased abundance of Akkermansia in patients with ulcerative colitis or Crohn’s disease, which was species and subspecies-dependent. In patients undergoing immune checkpoint inhibitor therapies for non-small cell lung carcinoma, we observed a significant association between one A. muciniphila subspecies and survival outcomes. Conclusion: Our findings suggest that the prevalence of specific Akkermansia species and/or subspecies can be crucial in evaluating their association with human health, particularly in different disease contexts, and is an important consideration for their use as probiotics.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 teacher head, 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".