A Metabolomics Approach To Identify Metabolites Associated with Uremic Symptoms in Patients Receiving Maintenance Hemodialysis
Bibliographic record
Abstract
Key Points Uremic symptoms are common in patients with kidney failure, but the chemicals causing them are unknown. We used state-of-the-art untargeted metabolomics and rigorous analyses to search for metabolites associated with uremic symptoms. We identified metabolite-symptom associations but could not replicate findings and offer recommendations for future research. Background The specific toxins causing uremic symptoms (nausea, vomiting, pruritus, fatigue, difficulty concentrating, and pain) in kidney failure remain unknown. We used untargeted metabolomics to identify plasma metabolites associated with uremic symptoms in patients receiving hemodialysis. Methods We measured metabolites in plasma samples from Longitudinal US/Canada Incident Dialysis study participants at baseline (discovery; n =636) and year 1 (internal validation; n =260) and from Frailty Assessment in Renal Disease study participants (external validation; n =355). We used metabolite-wise linear models with empirical Bayesian inference to evaluate the association between metabolites and uremic symptom severity, adjusting for key covariates. We accounted for multiple testing using a false discovery rate ( P values adjusted for false discovery rate [pFDR]) for linear models and used two machine learning models to evaluate the association consistency. We defined association as significant if pFDR < 0.1 and consistent if it had medium or high importance in both machine learning models. Results Participants had a mean age of 63 years, with uremic symptom prevalence ranging from 44% to 83%. We identified 627 previously characterized (known) and 35,558 unknown metabolite peaks. No known metabolites were significantly and consistently associated with uremic symptom severity across all cohorts. Within cohorts, retinol was negatively associated with nausea/vomiting in Longitudinal US/Canada Incident Dialysis at year 1, and indole-3-propionic acid was negatively associated with anorexia in Frailty Assessment in Renal Disease. Several unknown metabolites were associated with symptoms (lowest pFDR, 0.0004), but none were consistent across cohorts. Conclusions We identified metabolites associated with uremic symptom severity, although findings were inconsistent across cohorts. This study highlights the need for additional research on uremic toxins and clinical 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".