Desai, Perlina; (2025) Using proximity labelling to investigate astrocyte secretory pathway proteome alterations in Alzheimer's disease. Doctoral thesis (Ph.D), UCL (University College London).

Text Desai_PhD_Thesis.pdf - Accepted Version Access restricted to UCL open access staff until 1 August 2026. Download (22MB)

Abstract

Astrocytes are an abundant and diverse glial subtype specialised to maintain homeostasis and effective functioning of the central nervous system. They achieve this in part through tightly regulated protein secretion via the classical secretory pathway, enabling intercellular communication, metabolic support and immune modulation. In Alzheimer’s disease (AD), astrocytes are thought to adopt reactive states and contribute to neuroinflammation. A key feature of this reactive gliosis is the secretion of inflammatory mediators, which depending on context can be protective or detrimental to disease progression. However, at present, there remains a limited understanding of global astrocytic secretory pathway protein (SPP) profiles and potential changes associated with AD. In this study, I employed an unbiased proximity labelling-mass spectrometry-based approach to identify astrocytic SPPs in a physiological context. A viral construct encoding ER-retained TurboID under an astrocyte-specific GfaABC1D promoter was used to label SPPs in the AppNL-G-F AD mouse model and age-matched controls, across early and late stages of amyloid pathology. Following validation of the construct, I developed a computational pipeline for data pre-processing, and subsequently performed in-depth complementary bioinformatic analyses to investigate astrocytic SPP alterations associated with amyloid pathology. In doing so, I have identified distinct alterations in protein expression and dysregulation of key biological processes at different stages of amyloidosis. This research enhances our understanding of astrocytic molecular dysfunction associated with AD, which may ultimately aid in the identification of novel biomarkers and therapeutic targets for disease diagnosis and intervention.

Download activity - last month

Export as CSVXMLJSON

Download activity - last 12 months

Export as XMLCSVJSON

Downloads by country - last 12 months

Export as JSONXMLCSV

Archive Staff Only

View Item