Microbiomics, Metabolomics, Predicted Metagenomics, and Hepatic Steatosis in a Population‐Based Study of 1,355 Adults
Bibliographic record
Abstract
Background and Aims Previous small studies have appraised the gut microbiome (GM) in steatosis, but large‐scale studies are lacking. We studied the association of the GM diversity and composition, plasma metabolites, predicted functional metagenomics, and steatosis. Approach and Results This is a cross‐sectional analysis of the prospective population‐based Rotterdam Study. We used 16S ribosomal RNA gene sequencing and determined taxonomy using the SILVA reference database. Alpha diversity and beta diversity were calculated using the Shannon diversity index and Bray–Curtis dissimilarities. Differences were tested across steatosis using permutational multivariate analysis of variance. Hepatic steatosis was diagnosed by ultrasonography. We subsequently selected genera using regularized regression. The functional metagenome was predicted based on the GM using Kyoto Encyclopedia of Genes and Genomes pathways. Serum metabolomics were assessed using high‐throughput proton nuclear magnetic resonance. All analyses were adjusted for age, sex, body mass index, alcohol, diet, and proton‐pump inhibitors. We included 1,355 participants, of whom 472 had steatosis. Alpha diversity was lower in steatosis ( P = 1.1∙10 −9 ), and beta diversity varied across steatosis strata ( P = 0.001). Lasso selected 37 genera of which three remained significantly associated after adjustment ( Coprococcus3 : β = −65; Ruminococcus Gauvreauiigroup : β = 62; and Ruminococcus Gnavusgroup : β = 45, Q ‐value = 0.037). Predicted metagenome analyses revealed that pathways of secondary bile‐acid synthesis and biotin metabolism were present, and D‐alanine metabolism was absent in steatosis. Metabolic profiles showed positive associations for aromatic and branched chain amino acids and glycoprotein acetyls with steatosis and R. Gnavusgroup , whereas these metabolites were inversely associated with alpha diversity and Coprococcus3 . Conclusions We confirmed, on a large‐scale, the lower microbial diversity and association of Coprococcus and Ruminococcus Gnavus with steatosis. We additionally showed that steatosis and alpha diversity share opposite metabolic profiles.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".