Prediagnostic alterations in circulating bile acid profiles in the development of hepatocellular carcinoma
Bibliographic record
Abstract
Abstract Bile acids (BAs) play different roles in cancer development. Some are carcinogenic and BA signaling is also involved in various metabolic, inflammatory and immune‐related processes. The liver is the primary site of BA synthesis. Liver dysfunction and microbiome compositional changes, such as during hepatocellular carcinoma (HCC) development, may modulate BA metabolism increasing concentration of carcinogenic BAs. Observations from prospective cohorts are sparse. We conducted a study (233 HCC case‐control pairs) nested within a large observational prospective cohort with blood samples taken at recruitment when healthy with follow‐up over time for later cancer development. A targeted metabolomics method was used to quantify 17 BAs (primary/secondary/tertiary; conjugated/unconjugated) in prediagnostic plasma. Odd ratios (OR) for HCC risk associations were calculated by multivariable conditional logistic regression models. Positive HCC risk associations were observed for the molar sum of all BAs (OR doubling = 2.30, 95% confidence intervals [CI]: 1.76‐3.00), and choline‐ and taurine‐conjugated BAs. Relative concentrations of BAs showed positive HCC risk associations for glycoholic acid and most taurine‐conjugated BAs. We observe an association between increased HCC risk and higher levels of major circulating BAs, from several years prior to tumor diagnosis and after multivariable adjustment for confounders and liver functionality. Increase in BA concentration is accompanied by a shift in BA profile toward higher proportions of taurine‐conjugated BAs, indicating early alterations of BA metabolism with HCC development. Future studies are needed to assess BA profiles for improved stratification of patients at high HCC risk and to determine whether supplementation with certain BAs may ameliorate liver dysfunction.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".