Metabolomic identification of α-ketoglutaric acid elevation in pediatric chronic graft-versus-host disease
Bibliographic record
Abstract
Chronic graft-versus-host disease (cGVHD) is the most common cause for non-relapse mortality postallogeneic hematopoietic stem cell transplant (HSCT). However, there are no well-defined biomarkers for cGVHD or late acute GVHD (aGVHD). This study is a longitudinal evaluation of metabolomic patterns of cGVHD and late aGVHD in pediatric HSCT recipients. A quantitative analysis of plasma metabolites was performed on 222 evaluable pediatric subjects from the ABLE/PBMTC1202 study. We performed a risk-assignment analysis at day + 100 (D100) on subjects who later developed either cGVHD or late aGVHD after day 114 to non-cGVHD controls. A second analysis at diagnosis used fixed and mixed multiple regression to compare cGVHD at onset to time-matched non-cGVHD controls. A metabolomic biomarker was considered biologically relevant only if it met all 3 selection criteria: (1) P ≤ .05; (2) effect ratio of ≥1.3 or ≤0.75; and (3) receiver operator characteristic AUC ≥0.60. We found a consistent elevation in plasma α-ketoglutaric acid before (D100) and at the onset of cGVHD, not impacted by cGVHD severity, pubertal status, or previous aGVHD. In addition, late aGVHD had a unique metabolomic pattern at D100 compared with cGVHD. Additional metabolomic correlation patterns were seen with the clinical presentation of pulmonary, de novo, and progressive cGVHD. α-ketoglutaric acid emerged as the single most significant metabolite associated with cGVHD, both in the D100 risk-assignment and later diagnostic onset analysis. These distinctive metabolic patterns may lead to improved subclassification of cGVHD. Future validation of these exploratory results is needed. This trial was registered at www.clinicaltrials.gov as #NCT02067832.
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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) | 0.000 | 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 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".