Large-scale clinical phenotyping of cerebral small vessel disease: describing an expanding clinical spectrum

Kancheva, Angelina Kirilova (2026) Large-scale clinical phenotyping of cerebral small vessel disease: describing an expanding clinical spectrum. PhD thesis, University of Glasgow.

Abstract

Cerebral small vessel disease (cSVD) encompasses a group of pathologies affecting the small perforating vessels of the brain. It is a leading contributor to vascular cognitive impairment and a major cause of stroke and dementia. Other physical and psychological consequences include neuropsychiatric symptoms, sleep disturbance, and gait impairment. Despite improved standardisation of cSVD neuroimaging features, a comprehensive characterisation of its clinical phenotype remains limited. Clinical heterogeneity poses a particular challenge, as cSVD is often diagnosed only after overt pathology emerges, is managed across multiple clinical services, and similar imaging features may be associated with diverse clinical symptoms across individuals. A better description of the full clinical spectrum of cSVD is therefore essential to understand disease manifestations and inform treatment development. The aim of this thesis was to build on previous efforts to characterise the clinical spectrum of cSVD more comprehensively by integrating large-scale neuroimaging and clinical data from multiple multisite cohorts.

Chapter 1 introduces cSVD, its neuropathological mechanisms, neuroimaging features, and clinical manifestations. Chapter 2 presents an overview of systematic reviews summarising evidence on cSVD-related clinical phenotypes. Across 24 reviews encompassing 685 original studies and 1,135,943 participants, cognitive and neuropsychiatric phenotypes were examined most frequently, particularly in relation to white matter hyperintensities (WMHs), while other clinical manifestations and cSVD features were comparatively less studied.

Chapter 3 describes the results of a hypothesis-free imaging-based phenome-wide association study of WMH volume and clinical phenotypes in 45,013 UK Biobank (UKB) participants. Established associations with depression, apathy, respiratory problems, and sleep disturbance were confirmed, alongside less well-described associations with dental issues, hearing difficulties, and eye problems. Building on this work, Chapter 4 examines baseline phenotypes associated with WMH volume change over a median of 2.3 years in 4329 UKB participants. It further explores which phenotypes might help classify individuals into three WMH trajectory groups, namely WMH progressors, WMH regressors, and those in whom WMHs remain stable. WMHs were found to progress in some, regress in other, and remain stable in a third group of individuals, with differing demographic and vascular associations with WMH volume change. Chapter 5 extends these findings to the Lothian Birth Cohort 1936 using structural equation modelling, focusing on phenotypes that were relatively novel or underexplored in the UKB analyses and wider literature. Higher WMH volume was associated with fewer teeth and poorer mobility, including shorter demi-span and slower walking speed.

Finally, given increasing evidence that vascular and neurodegenerative pathologies often coexist, Chapter 6 explores cardiovascular risk as a moderator of the association between Alzheimer’s disease–related blood plasma biomarkers and cognitive status in the Bio-Hermes cohort. Cardiovascular risk and biomarkers of interest were independently associated with cognition, while moderation effects were observed for phosphorylated tau (p-tau)181 and p-tau217.

Finally, Chapter 7 brings all findings together, discussing overarching learnings and contributions of this thesis, as well as limitations, and provides directions for future research.

By adding to a more detailed description of the clinical footprint of cSVD, including in the shared context of vascular and neurodegenerative brain pathology, this thesis demonstrates that cSVD is a dynamic, multisystem syndrome with an expanding and heterogeneous clinical spectrum. Findings highlight the need for integrated, multidisciplinary approaches to research and clinical management, improved stratification of risk groups, and multimodal data integration to inform future clinical trials and targeted interventions.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Additional Information: Supported by funding from the Medical Research Council Doctoral Training Program (MRC DTP) in Precision Medicine.
• Subjects: R Medicine > R Medicine (General); R Medicine > RC Internal medicine
• Colleges/Schools: College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health
• Funder's Name: Medical Research Council (MRC)
• Supervisor's Name: Quinn, Professor Terry, Lyall, Dr. Donald and Wardlaw, Professor Joanna
• Date of Award: 2026
• Depositing User: Theses Team
• Unique ID: glathesis:2026-85994
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 10 Jun 2026 08:55
• Last Modified: 10 Jun 2026 15:48
• Thesis DOI: 10.5525/gla.thesis.85994
• URI: https://theses.gla.ac.uk/id/eprint/85994

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