Elevated A2F bisect N-glycans of serum IgA reflect progression of liver fibrosis in patients with MASLD
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Bibliographic record
Abstract
BACKGROUND: Advanced liver fibrosis in cases of metabolic dysfunction-associated steatotic liver disease (MASLD) leads to cirrhosis and hepatocellular carcinoma. The current gold standard for liver fibrosis is invasive liver biopsy. Therefore, a less invasive biomarker that accurately reflects the stage of liver fibrosis is highly desirable. METHODS: This study enrolled 269 patients with liver biopsy-proven MASLD. Patients were divided into three groups (F0/1 (n = 41/85), F2 (n = 47), and F3/4 (n = 72/24)) according to fibrosis stage. We performed serum N-glycomics and identified glycan biomarker for fibrosis stage. Moreover, we explored the carrier proteins and developed a sandwich ELISA to measure N-glycosylation changes of carrier protein. RESULTS: Comprehensive N-glycomic analysis revealed significant changes in the expression of A2F bisect and its precursors as fibrosis progressed. The sum of neutral N-glycans carrying bisecting GlcNAc and core Fuc (neutral sum) had a better diagnostic performance to evaluate advanced liver fibrosis (AUC = 0.804) than conventional parameters (FIB4 index, aspartate aminotransferase-to-alanine aminotransferase ratio (AAR), and serum level of Mac-2-binding protein glycol isomer (M2BPGi). The combination of the neutral sum and FIB4 index enhanced diagnostic performance (AUC = 0.840). IgM, IgA, and complement C3 were identified as carrier proteins with A2F bisect N-glycan. A sandwich ELISA based on N-glycans carrying bisecting GlcNAc and IgA showed similar diagnostic performance than the neutral sum. CONCLUSIONS: A2F bisect N-glycan and its precursors are promising candidate biomarkers for advanced fibrosis in MASLD patients. Analysis of these glycan alterations on IgA may have the potential to serve as a novel ELISA diagnostic tool for MASLD in routine clinical practice. CLINICAL TRIAL NUMBER: UMIN000030720.
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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 | 0.000 | 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 it