Industrialization drives convergent microbial and physiological shifts in the human metaorganism
Bibliographic record
Abstract
Understanding how host lifestyle and industrialization shape the human gut microbiome and intestinal physiology requires multimodal analyses across diverse global host contexts. Here, we generate multivariate data from the Global Microbiome Conservancy cohort, including gut microbiome, IgA-sequencing, host genotyping, diet, lifestyle and fecal biomarker profiles, to investigate host-microbiome interactions across gradients of industrialization and geography. We show that industrialization is associated with homogenized microbial compositions, reduced microbial diversity, and lower community stability, independent of host confounders. We further show that industrialization is linked to elevated markers of gut stress, increased IgA secretion, and altered patterns of IgA-bacteria interactions. Finally, we show that microbiome-based disease predictors trained on industrialized populations lose accuracy in less industrialized cohorts, highlighting limited cross-population transferability. Together, our results suggest profound restructuring of host-microbiome interactions due to industrialized lifestyles, and emphasize the need for inclusive, globally representative data to improve translational microbiome applications across diverse human populations.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".