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The genetics of dementia progression and heterogeneity

Scelsi, Marzia Antonella; (2020) The genetics of dementia progression and heterogeneity. Doctoral thesis (Ph.D), UCL (Univeristy College London). Green open access

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Abstract

Dementia is a progressive neurodegenerative disorder of the elderly that spans decades, with pathological changes occurring in the brain long before symptoms onset. Dementia is also an umbrella term encompassing multiple syndromes with clinical presentations overlapping to varying extents. Even within the most common type of dementia, Alzheimer's disease (AD), there is evidence for heterogeneity and complex progression patterns. An added level of complexity comes from an incomplete knowledge of the genetics of AD as a whole, and uncertainty as to whether or not progression and heterogeneity are modified by genetic risk factors. This ultimately results in a plethora of failed clinical trials, with only four molecules approved for symptoms management but none as disease-modifying treatment. Integrating this complexity into standard genetic association mapping is crucial to understand how genetic variation contributes to progression patterns, how it relates to comorbidities and drives the differentiation of dementia in syndromes and subtypes, and how it affects protein interactions that result in observable phenotypes. This knowledge would help informing enrichment and stratification in clinical trials, providing evidence for repurposing of existing medications and suggesting novel drug targets. Towards these ends, this thesis provides the following contributions: I performed a genetic association study of AD progression, modelled by integrating longitudinal imaging biomarkers, and demonstrated how disease progression can be modified by genetic factors through discovery and validation in two independent datasets; I performed a genetic association study of a rare dementia syndrome, posterior cortical atrophy (PCA), in comparison to amnestic AD, identifying and attempting validation of genetic loci that modulate risk for this rare syndrome over amnestic AD; I performed a genetic association study of data-driven AD subtypes, derived by integrating longitudinal imaging biomarkers into a subtyping and staging technique, linking a specific subtype to genetic risk for type 2 diabetes through multiple lines of evidence; I developed a computational framework that models percolation of effects from rare damaging mutations through gene interaction networks, to identify gene hubs where these effects converge as potential drug targets; I validated the findings in two independent datasets and performed extensive simulations and bioinformatics analyses to demonstrate robustness and biological plausibility of the results.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: The genetics of dementia progression and heterogeneity
Event: UCL
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Copyright © The Author 2020. Original content in this thesis is licensed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) Licence (https://creativecommons.org/licenses/by/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10101305
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