Glycan Age Prediction Model

Abstract

Researchers at the University of California, Davis, have developed a model to estimate biological and chronological age from blood serum samples.

Full Description

Alterations in the human glycome have been associated with cancer and autoimmunity. Thus, constructing a site-specific map of the human glycome for biomarker research and discovery has been a highly sought-after objective. However, due to analytical barriers, comprehensive site-specific glycoprofiling is difficult to perform.

Researchers at the University of California, Davis have developed a platform to detect easily quantifiable, site-specific, disease-associated glycan alterations for clinical applications by adapting the Multiple Reaction Monitoring (MRM) Mass Spectrometry (MS) method for use in glycan biomarker research. The adaptations allow for highly precise site-specific glycan monitoring with minimum sample preparation. MRM MS was employed to construct a detailed, site-specific structural map of the human plasma glycome of healthy individuals and to characterize the glycans’ inter- and intra-molecular correlations. Glycan alterations associated with age and gender (common covariants in biomarker research and discovery) were also identified and multi-analyte classifiers capable of predicting age were constructed and validated.

Applications

• Glycan biomarker research and discovery. 
• Development of novel glycan-altering therapeutics.

Features/Benefits

• Characterize the human glycome in a rapid and reproducible fashion. 
• Detects quantifiable, site-specific, disease-associated glycan alterations more efficiently than previous glycan age prediction models.

Patent Status