Methylglyoxal-Induced Glycation of Plasma Albumin: From Biomarker Discovery to Clinical Use for Prediction of New-Onset Diabetes in Individuals with Prediabetes
Bibliographic record
Abstract
BACKGROUND: Methylglyoxal (MGO) is a potent glycating agent that contributes to the pathogenesis of diabetes. However, MGO is unstable in plasma without demanding sample preparation at blood collection, limiting its clinical utility as a biomarker. We aimed to discover reliable MGO-glycated albumin (ALB)-derived biomarkers and to assess their association with new-onset diabetes (NOD) in people with prediabetes. METHODS: Bottom-up mass spectrometry-based proteomics was used to discover peptide biomarkers of MGO-glycated ALB, including MGO-derived hydroimidazolone (MGH)-ALB219-225, which proved to be biologically stable and reliable for large-scale analyses in human plasma. After assay validation, the IT-DIAB (Innovation Thérapeutique DIABète) prospective study, conducted in 300 individuals with impaired fasting plasma glucose (FPG) levels (110 to 125 mg/dL, 6.1 to 6.9 mmol/L), was used to assess the association between plasma MGH-ALB219-225 and NOD, defined as FPG ≥126 mg/dL (7 mmol/L), using Kaplan-Meier curves and Cox models. RESULTS: In total, 113 participants of the IT-DIAB study developed NOD during a median follow-up of 5 years. There was a graded association between the baseline plasma MGH-ALB219-225 concentration and incident NOD (log-rank P < 0.0001), in contrast to a lack of association for plasma MGO and total or glycated ALB (commercial kit). After adjustment for age, sex, body mass index, FPG, hemoglobin (Hb) A1c, and ALB, the plasma levels of MGH-ALB219-225 were associated with NOD (hazard ratio [HR] per one SD [95% CI] = 1.50 [1.26-1.78]; P < 0.0001). CONCLUSIONS: MGH-ALB219-225 is a novel and stable peptide biomarker of MGO-glycated ALB, whose plasma levels are positively associated with an increased risk of NOD in individuals with prediabetes, independently of traditional risk factors. ClinicalTrials.gov Registration Number: NCT01218061.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".