Taming the masses: Proteomic profiling across the spectrum and stages of neurodegenerative diseases

Abstract

Neurodegenerative diseases (NDs) are a group of brain-related disorders that mainly affect individuals of older age. They are characterized by a progressive loss of neurons, which ultimately results in a wide array of clinical symptoms such as dementia, personality changes or walking difficulties. An aging population in many countries has transformed NDs into one of our biggest health challenges, as they are largely untreatable to date. A hallmark feature of NDs is the aggregation of specific proteins into inclusions. Each ND is defined by characteristic aggregating proteins, affected brain regions and other factors. Despite distinct pathological features, symptoms across different NDs overlap, posing a significant challenge to accurate clinical diagnosis. A reliable and early diagnosis, as well as the ability to stage and track the disease course, however, are prerequisites to successful clinical trials. Fluid biomarkers, objective markers measured in the cerebrospinal fluid (CSF) or blood of patients, are regarded as highly promising tools to address these very challenges. This thesis aimed to identify novel CSF biomarker candidates for two of the most common NDs, Alzheimer’s disease (AD) and frontotemporal dementia (FTD), using mass spectrometry (MS)-based proteomics with an optimized tandem mass tag (TMT) protocol. Additionally, targeted MS-based assays were developed for the quantification of biomarker candidates of interest. Following the careful evaluation of different aspects of a TMT workflow, an analytical strategy based on in-solution digestion, MS2-based peptide quantification and median normalization was chosen for future clinical proteomic studies. A key finding from TMT proteomic data across three large AD case-control studies was that disease-associated CSF protein levels fluctuate dynamically with AD progression. Distinct protein groups reflecting different pathophysiological processes changed sequentially, highlighting their utility in disease staging. Additionally, proteins linked to neurodegeneration and inflammation strongly correlated with AD neuropathology, suggesting their potential as imaging surrogates. This thesis also demonstrated that the emerging biomarker candidate secernin-1 (SCRN1), quantified using a newly developed targeted MS assay in CSF, was selectively elevated in AD patients compared with controls and those with other parkinsonism-related NDs. Future studies are warranted to explore its potential as an AD biomarker, particularly in the context of cognitive resilience. A TMT study in a large cohort of presymptomatic and symptomatic genetic FTD patients, including three mutation types and controls, revealed that subtle CSF proteomic changes are detectable already at the presymptomatic stage, with identified proteins holding potential as prognostic biomarkers. In symptomatic individuals, more widespread proteomic changes were observed, with significant overlap across mutation subgroups. Notably, the study identified lysosome-related CSF proteins that may differentiate between the two major pathological FTD subtypes, a finding that could improve diagnosis and patient stratification for clinical trials. Lastly, this thesis includes the development of a targeted MS assay for measuring endogenous granulins in CSF. Granulins are potential biomarkers for a subset of FTD patients with progranulin (GRN) mutation, which causes reduced progranulin protein levels in CSF and as shown in this thesis, reduced levels of its cleavage products, the granulins. Applying this assay in clinical trials aiming to restore progranulin levels could provide insights into how these cleavage products respond to treatment. In conclusion, this thesis work presents (i) practical guidelines for the performance of TMT proteomic experiments in CSF, (ii) CSF proteomic profiles across the AD continuum as well as genetic FTD spectrum and, finally, (iii) the development and application of novel MS-based assays to measure AD- and GRN-FTD-related biomarker candidates in CSF.