Biomarker discovery in diabetes mellitus and lipid metabolism: multi-platform glyco(proteo)mic approaches

Abstract

The aim of the research presented in this thesis is development and optimization of analytical methods to study glycosylation changes as potential stratification biomarkers in large clinical sample cohorts of patients with two types of diabetes and diabetes-related complications. The analytical workflows proposed in this research were designed to address and overcome challenges in areas of high-throughput sample preparation, the analysis of these samples, subsequent data processing and statistical analysis. The developed methods are applicable for the analysis of released N-glycans, O-glycosylated proteins and absolute fucosylation levels of proteins derived from blood plasma.

In the final chapter, research studies presented in this thesis are discussed and the research findings critically evaluated in the context of their significance for clinical use. Aspects that pose a challenge in translating glycan biomarkers into clinical practice are highlighted. Moreover, the potential of analytical methods and statistical approaches employing large omics data, which are proposed in this thesis, is evaluated for its use in the biopharma industry.