Investigation of <i>N</i>,<i>N</i>,<i>N</i>-Trimethyl-L-alanyl-L-proline Betaine (TMAP) as a Biomarker of Kidney Function
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Glomerular filtration rate (GFR) is the most widely used tool for the measurement of kidney function, but endogenous biomarkers such as cystatin C and creatinine have limitations. A previous metabolomic study revealed N, N, N -trimethyl-L-alanyl-L-proline betaine (TMAP) to be reflective of kidney function. In this study, we developed a quantitative LCMS assay for the measurement of TMAP and evaluated TMAP as a biomarker of GFR. An assay to measure TMAP was developed using liquid chromatography-mass spectrometry. After validation of the method, we applied it to plasma samples from three distinct kidney disease patient cohorts: nondialysis chronic kidney disease (CKD) patients, patients receiving peritoneal and hemodialysis, and living kidney donors. We investigated whether TMAP was conserved in other mammalian and nonmammalian species, by analyzing plasma samples from Wistar rats with diet-induced CKD and searching for putative matches to the m/z for TMAP and its known fragments in the raw sample data repository “Metabolomics Workbench”. The assay can measure plasma TMAP at a lower limit of quantitation (100 ng/mL) with an interday precision and accuracy of 12.8 and 12.1%, respectively. In all three patient cohorts, TMAP concentrations are significantly higher in patients with CKD than in controls with a normal GFR. Further, TMAP concentrations are also elevated in rats with CKD and TMAP is present in the sap produced from Acer saccharum trees. TMAP concentration is inversely related to GFR suggesting that it is a marker of kidney function. TMAP is present in nonmammalian species suggesting that it is part of a biologically conserved process.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 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".