Pavisic, Ivanna Micol;
(2021)
Detecting and tracking populations at-risk of Alzheimer’s disease: studying asymptomatic cognitive profiles and symptomatic clinical presentations.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
Familial Alzheimer’s disease (FAD) is a penetrant autosomal dominantly inherited condition. Due to its clinical and neurophysiological similarities with sporadic AD features, it represents an important clinical group in its own right but also offers a potential model for AD. This thesis is largely based on the longitudinal FAD study but also includes data from ‘Insight 46’ in an attempt to broaden the scope of these investigations to other ‘at-risk’ cohorts. The overarching aim of the thesis is to study the early subtle cognitive changes (with a particular focus on visual short-term memory but also subjective cognitive decline) and the symptomatic presentations (both cognitive and clinical) that accompany disease progression in AD. The key findings were that over time, presymptomatic mutation carriers (PMCs) had a faster rate of decline in visual short-term memory (VSTM) function, specifically in the ability to remember the location and the target identity. This relational binding deficit was strongest in the most challenging task condition: 3-items, 4s delay (high load, longest delay), and is clinically relevant as it shows sensitivity in tracking individuals during preclinical AD stages. Consequent eye movement investigations of VSTM function, revealed a stronger cognitive effort for PMCs compared to controls during encoding, a finding which may increase the diagnostic value of relational binding tasks. Other important findings were: the higher incidence of subjective cognitive decline symptoms in two otherwise different populations “at-risk” of AD: PMCs carriers and amyloid-positive ~70-year-old participants and the ineffective VSTM function and much smaller influence of mutation specificity on survival time variance in comparison to variance in age at onset for symptomatic FAD individuals. Together, this work has implications for the interpretation of cognitive and clinical data, the understanding of heterogeneity in FAD and may help detect and track subtle cognitive decline of potential value to clinical practice.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Detecting and tracking populations at-risk of Alzheimer’s disease: studying asymptomatic cognitive profiles and symptomatic clinical presentations |
| Event: | UCL (University College London) |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2021. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/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 > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Neurodegenerative Diseases |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10128600 |
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