113 Distinct brain MRI phenotypes and their association with long-term dementia risk 6 6.2 INTRODUCTION Most older adults have brain changes on MRI, such as cerebral atrophy or manifestations of cerebral small vessel disease (SVD).1 These brain MRI markers mostly represent late resulting damage of different underlying pathologies and are therefore largely unspecific. This makes differentiation of underlying pathology based on brain MRI challenging.1 Moreover, some brain abnormalities detected on MRI are regarded as related to normal ageing. It is currently unknown if specific brain MRI phenotypes represent an increased risk for dementia. The ability to determine an individual’s risk for dementia based on MRI may in the future be useful to determine patient prognosis and may aid in patient selection for future treatment studies. Common brain MRI markers of neurovascular and neurodegenerative diseases are white matter hyperintensities (WMHs), lacunes, microbleeds, enlarged perivascular spaces, and cerebral atrophy. These brain MRI markers have been studied previously and are associated with the occurrence of dementia.2-6 However, individual brain MRI markers only show at best a modest association with long-term occurrence of dementia.4 It, therefore, remains challenging to identify individuals who are at increased risk to develop dementia.2 Because of heterogenous etiology and mixed pathologies, methods combining different brain MRI markers into one model may likely aid in a more detailed characterization of, potential prognostically relevant, so-called brain MRI phenotypes. In a previous study within our group (in a different cohort), we aimed to detect an increased stroke and mortality risk in patients with manifest arterial disease and analyzed brain MRI markers in a combined way using a hierarchical clustering approach, resulting in the identification of different brain MRI phenotypes.7 In that study, distinct brain MRI phenotypes were detected that were associated with a different risk of future stroke and mortality. These brain MRI phenotypes can aid to identify the structural correlates of predisposition to different disease outcome. The association of distinct brain MRI phenotypes with long-term dementia risk remains unknown. We therefore aimed to identify different brain MRI phenotypes in community-dwelling individuals by combined hierarchical clustering analysis based on neurovascular and neurodegenerative brain MRI markers. Within each of these brain MRI phenotype subgroups, we determined the long-term dementia risk. 6.3 METHODS 6.3.1 Participants and study design The data set used for the current analysis was acquired as part of the population based Age-Gene/Environment Susceptibility (AGES) Reykjavik Study.8 The cohort study was originally established in 1967 to prospectively study cardiovascular disease
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