Alterations in Urine Metabolomics Following Sport-Related Concussion: A 1H NMR-Based Analysis
Bibliographic record
Abstract
Objective: Millions of sport-related concussions (SRC) occur annually in North America, and current diagnosis of concussion is based largely on clinical evaluations. The objective of this study was to determine whether urinary metabolites are significantly altered post-SRC compared to pre-injury. Setting: Outpatient sports medicine clinic. Participants: Twenty-six male youth sport participants. Methods: Urine was analyzed pre-injury and after SRC by 1H NMR spectroscopy. Data were analyzed using multivariate statistics, pairwise t-test, and metabolic pathway analysis. Variable importance analysis based on random variable combination (VIAVC) was applied to the entire data set and resulted in a panel of 18 features. Partial least square discriminant analysis was performed exploring the separation between pre-injury and post-SRC groups. Pathway topography analysis was completed to identify biological pathway involvement. Spearman correlations provide support for the relationships between symptom burden and length of return to play and quantifiable metabolic changes in the human urinary metabolome. Results: Phenylalanine and 3-indoxysulfate were upregulated, while citrate, propylene glycol, 1-methylhistidine, 3-methylhistidine, anserine, and carnosine were downregulated following SRC. A receiver operator curve (ROC) tool constructed using the 18-feature classifier had an area under the curve (AUC) of 0.887. A pairwise t-test found an additional 19 altered features, 7 of which overlapped with the VIAVC analysis. Pathway topology analysis indicated that aminoacyl-tRNA biosynthesis and beta-alanine metabolism were the two pathways most significantly changed. There was a significant positive correlation between post-SRC 2-hydroxybutyrate and the length of return to play (ρ = 0.482, p = 0.02) as well as the number of symptoms and post-SRC lactose (ρ = 0.422, p = 0.036). Conclusion: We found that 1H NMR metabolomic urinary analysis can identify a set of metabolites that can correctly classify SRC with an accuracy of 81.6%, suggesting potential for a more objective method of characterizing SRC. Correlations to both the number of symptoms and length of return to play indicated that 2-hydroxybutyrate and lactose may have potential applications as biomarkers for sport-related concussion.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".