Deciphering the Alzheimer's disease glyco-code
MentorJoseph Zaia, PhD
Alzheimer's disease (AD) is a leading cause of dementia, involving cognitive decline, loss of independence and behavioral issues. Identifying the biomolecular deregulation associated with AD is crucial to decode the underpinning disease mechanisms, to discover new biomarkers, and to improve treatment strategies. This project will utilize an analytical workflow, allowing the exploration of the structure and biology of proteins and glycans in AD from patient tissue specimens. Outcomes of this project will benefit AD patients by generating the fundamental, previously unattainable, glycobiological knowledge required to improve the diagnosis and treatment of AD.
The current understanding of Alzheimer’s disease (AD) pathology is not sufficient to provide new prevention or disease therapies. It is therefore, crucial to understand molecular alterations related to AD to better understand disease pathology. Emerging evidence supports the association of extracellular matrix (ECM) molecules, including proteoglycans (PGs), and glycosaminoglycans (GAGs) with AD, a neglected topic. We and others have demonstrated the power of mass spectrometry proteomics and glycomics to identify altered biomolecules and determine their roles in disease mechanisms. In this project, we will utilize analytical workflows to extract GAGs and PGs from tissue biospecimens from patients, and perform detailed structural analysis using mass spectrometry to establish functional relationship and explore the critical roles of these ECM structures in AD. The study aims to achieve two goals: firstly, to identify the structural differences in the PGs and GAGs that occur in AD pathology necessary to understand the underlying molecular mechanisms; secondly, to develop the identified altered PG (and GAG) structures as clinical markers for early detection of AD and assess therapeutic potential as drug targets. Outcomes of this project will benefit AD patients by generating the fundamental knowledge required to improve the diagnosis and treatment of AD.