Received on January 9, 2007
Accepted on April 26, 2007

Proteomics and Protein Markers

High-Throughput Quantitative Profiling of Serum N-Glycome by MALDI-TOF Mass Spectrometry and N-Glycomic Fingerprint of Liver Fibrosis

¹ Li Ka Shing Institute of Health Sciences, and Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR
² Li Ka Shing Institute of Health Sciences, and Department of Medicine and Therapeutics, and Centre for Emerging Infectious Diseases, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR
³ Department of Medicine and Therapeutics, and Centre for Emerging Infectious Diseases, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR
⁴ Department of Anatomical and Cellular Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR
⁵ Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR

^* To whom correspondence should be addressed. E-mail: tcwpoon{at}cuhk.edu.hk.

Background: The use of MALDI-TOF mass spectrometry (MS) in quantitative glycan profiling has not been reported. In this study, we attempted to establish a high-throughput quantitative assay for profiling serum N-glycome, and we applied the new assay to identifying serum N-glycans for diagnosis of liver fibrosis and cirrhosis.

N-Glycans from whole serum proteins in 2 µL serum were released by enzymatic digestion, cleaned up by hydrophilic chromatography, and subsequently quantitatively profiled with a linear MALDI-TOF MS system, which was originally designed for quantitative proteomic profiling. Serum N-glycome profiles from 46 patients with chronic hepatitis B infection and with different degrees of liver fibrosis were examined.

Results: The intra- and interassay CVs of peak intensities of the standard N-glycans were <8% and <17%, respectively. When the assay was applied to the analysis of serum N-glycome profiles, 17 peaks were found to be potential biomarkers for detection of liver fibrosis/cirrhosis. Linear regression analysis revealed that 4 peaks of 1341.5, 1829.7, 1933.3, and 2130.3 m/z (all P <0.005) had complementary value in detecting liver fibrosis and included them, but not any serological markers, in the diagnostic model. Leave-one-out cross-validation showed the diagnostic model could identify significant fibrosis (Ishak score 3) and cirrhosis (Ishak score 5), both at 85% accuracy.

Conclusion: This is the first study to illustrate the quantitative aspect of MALDI-TOF MS in N-glycome profiling and the first study to reveal the potential value of the serum N-glycan profile for identifying liver fibrosis.