Human serum albumin profiling by top-down analysis enables multi-class liver fibrosis staging: a cross-platform validation study.

Chronic liver disease (CLD) affects millions worldwide, yet accurately staging its progression without liver biopsy remains a major clinical challenge. Human serum albumin (HSA), the most abundant blood protein synthesized exclusively by the liver, undergoes measurable structural modifications as liver disease advances, making it a potential molecular marker of disease severity. Using high-resolution liquid chromatography-mass spectrometry (LC-HR-MS), we quantified native HSA and nine modified isoforms in plasma from 172 CLD patients spanning all fibrosis stages and 82 healthy controls. Native HSA declined markedly with disease severity, reaching 4.1-4.2 g/L in decompensated cirrhosis versus 12.2 g/L in controls. Modified isoforms showed stage-specific patterns, and their ratios to native HSA amplified the diagnostic signal for advanced disease. A machine learning classifier trained on the full albumin spectral profile achieved substantial agreement with standard staging, and demonstrated higher accuracy than FIB-4 index (81.5% vs. 59.3% accuracy). Within the study cohort, these results were reproduced on two independent instruments from different manufacturers (McNemar p = 0.149), confirming the reproducibility across different platforms of the albumin signature. These findings establish HSA spectral profiling as a promising non-invasive staging tool for CLD, with cross-platform reproducibility supporting its potential for translation to multicenter clinical practice.