Perturbations in human bile acid profiles following drug‐induced liver injury investigated using semitargeted high‐resolution mass spectrometry
Bibliographic record
Abstract
RATIONALE: Acetaminophen (APAP) overdose is the leading cause of acute liver failure (ALF) in North America. To investigate the effect of drug-induced liver injury (DILI) on circulating bile acid (BA) profiles, serum from ALF patients and healthy controls were analyzed using a semitargeted high-resolution mass spectrometry approach to measure BAs in their unconjugated and amidated forms and their glucuronide and sulfate conjugates. METHODS: Human serum samples from 20 healthy volunteers and 34 ALF patients were combined with deuterated BAs and extracted, prior to liquid chromatography high-resolution tandem mass spectrometry analysis. A mix of 46 standards helped assign 26 BAs in human serum by accurate mass and retention time matching. Moreover, other isomers of unconjugated and amidated BAs, as well as glucuronide and sulfate conjugates, were assigned by accurate mass filtering. In vitro incubations of standard BAs provided increased information for certain peaks of interest. RESULTS: A total of 275 BA metabolites, with confirmed or putative assignments, were measured in human serum samples. APAP overdose significantly influenced the levels of most BAs, promoting glycine conjugation, and, to a lesser extent, taurine conjugation. When patient outcome was considered, 11 BAs were altered significantly, including multiple sulfated species. Although many of the BAs measured did not have exact structures assigned, several putatively identified BAs of interest were further characterized using in vitro incubations. CONCLUSION: An optimized chromatographic separation tailored to BAs of ranging polarities was combined with accurate mass measurements to investigate the effect that DILI has on their complex profiles and metabolism to a much wider extent than previously possible. The analysis of complex BA profiles enabled in-depth analysis of the BA metabolism perturbations in ALF, including certain metabolites related to patient outcomes.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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".