As our life expectancy rises, the prevalence of common age-related brain diseases such as cognitive decline, dementia and neurovascular disease will increase. Effective preventive and curative interventions are scarce, whilst causative factors remain largely unknown. The role of cerebral white matter in age-related diseases has been established. However, macrostructural white matter changes, which are visible on a conventional MRI, constitute only the tip of the iceberg of the white matter pathology that have occurred. Recently, it has become possible to investigate white matter microstructural changes, thought of as an earlier and more sensitive markers, using Diffusion-Tensor-Imaging (DTI). It is hypothesized that white matter microstructural damage lead to loss of communication between different cortical networks, resulting in ‘disconnectivity’ leading to age-related brain diseases. Population data on determinants of white matter microstructural changes globally but in particular in specific white matter tracts in middle-aged and elderly persons were scarce.
The aims of the studies described in this thesis were to study determinants of global and tract-specific white matter microstructural damage, and to investigate the link between white matter microstructural damage and age-related brain diseases. The studies were embedded within the Rotterdam Study, which is a large population-based cohort study since 1990, investigating causes and consequences of diseases in the elderly.
To establish reference values of change in DTI measures in aging we performed a longitudinal analysis and found loss of white matter microstructural integrity widespread in the brain after 2 years of follow-up. Reduced kidney function and reduced lung function related to a lower white matter microstructural integrity. We found an age-dependent effect in the relation of thyroid hormones and white matter microstructure. Higher FT4 levels were associated with larger brain volumes and higher white matter microstructural integrity in younger individuals, but not in the elderly. We also found that white matter microstructure related to lower cognitive performance, mild cognitive impairment, hearing acuity, dementia, and mortality. We found differences across different tracts, The white matter microstructure of the association tracts related most often to the different outcomes. We tried to make the first step to the clinical implication of brain imaging markers and aimed to evaluate a previously proposed prediction tool namely the Disease State Index (DSI) to predict cognitive decline using imaging and non-imaging features. Best performance of the prediction of global cognitive decline was obtained using only age as input feature. Adding additional imaging markers did not improve prediction. This calls for other prediction tools, more advanced imaging markers or other analytical approaches in the prediction of age-related diseases.

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M.W. Vernooij (Meike) , M.A. Ikram (Arfan)
Erasmus University Rotterdam

Cremers, L. (2018, June 26). Structural Brain Connectivity in Aging and Neurodegeneration. Retrieved from