Metabolic profiling for water-soluble metabolites in patients with schizophrenia and healthy controls in a Chinese population: A case-control study
Bibliographic record
Abstract
Objectives: Objective measures integrated with clinical symptoms may improve early prevention and detection of schizophrenia. Herein we aim to evaluate potential water-soluble metabolic biomarkers in schizophrenia.Methods: We recruited adults with schizophrenia (n = 113) who had not received pharmacological treatment for at least 1 month prior to enrollment and 111 age- and sex-matched healthy subjects from Weifang, Shandong province, China. All serum samples were analysed using liquid chromatography-tandem mass spectrometry coupled with a hydrophilic interaction liquid chromatography column.Results: Eleven metabolites, namely carnitines (oleoylcarnitine, l-palmitoylcarnitine, 9-decenoylcarnitine and 2-trans,4-cis-decadienoylcarnitine), polar lipids (lysophosphatidylcholine (LPC)(P-16:0), LPC (16:0), LPC (15:0) and LPC(14:0)), amino acids (taurine and l-arginine), and organic acid (2,5-dichloro-4-oxohex-2-enedioate), separated the patients and healthy controls. Compared with healthy controls, taurine, l-palmitoylcarnitine and oleoylcarnitine levels were higher, whereas the remaining eight metabolites were lower in patients with schizophrenia. A combination of four metabolites, i.e., oleoylcarnitine, 9-decenoylcarnitine, LPC (15:0) and LPC (14:0), provided the most robust between-group separation.Conclusions: This study appears to distinguish between groups of patients and controls, which should be considered as a contribution to putative potential biomarkers. The water-soluble metabolites were determined to be significantly different between the groups in the current study, and were primarily related to cellular bioenergetics, notably oxidative stress.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".