Approved Research

Prediction of vascular cognitive impairment by exploiting novel imaging markers of brain network characteristics.

Lay summary

Dementia is highly frequent in ageing western societies. It has devastating effects as it reduces the wellbeing of affected individuals, leading to loss of independence in daily living. One of the major causes of dementia and cognitive decline is a condition called cerebral small vessel disease (CSVD). It leads to a slowly progressing damage of small brain blood vessels that in turn lead to diminish cognitive functions. CSVD is common in individuals in who vascular risk factors are present (i. e. high blood pressure, smoking or increased blood cholesterol levels).

We regard the human brain as a network of specialized brain areas that are connected to generate cognitive functions such as memory, orientation or attention. Vascular damage in CSVD disturbs these large-scale brain networks and therefore impedes normal brain functions. The underlying mechanisms are, however, poorly understood. We will investigate relationship of CSVD and brain network characteristics. Our project will have two major aims: 1) characterize the negative influence of CSVD on the so called cerebral cortex (where brain functions are generated) and the white matter (neurons that connect brain areas and allow information transfer). 2) Investigate which elements of the brain network are most vulnerable and therefore key elements for cognitive impairment in individuals with CSVD. We will observe changes in brain structure and function over time to detect relevant factors that can be used at early stages of CSVD to predict risk for cognitive impairment. The analysis will take into account known risk factors for vascular cognitive impairment and blood markers that signal increased risk for CSVD, such as high levels of cholesterol. We plan to conduct this project over a period of two years. By characterizing brain networks affected by CSVD, our work will benefit public health by providing novel risk markers for cognitive impairment and dementia. This will lead to a better understanding of vascular cognitive impairment and improved early detection of individuals at risk who can be targeted by timely individualized prevention.

Scope extension:

This project aims to investigate the predictive capacity of innovative brain imaging markers of brain network characteristics regarding vascular cognitive impairment (VCI). We will focus on novel measures of functional and structural large-scale-brain network topology and dynamics. Predictive value of imaging markers will be adjusted for known risk factors of VCI.  Our aim is to identify early risk markers in brain imaging supporting timely identification of individuals at risk for VCI and to guide future studies of early preventive measures. We plan to focus our investigation on cerebral small vessel disease (CSVD) as the most common cause of vascular cognitive impairment.

Questions to be addressed are:

*            How does CSVD in early and progressive stages alter cerebral white matter microstructure, cortical atrophy and topology of large-scale brain networks?

*            Does cortical atrophy in CSVD preferentially occur in network hubs, brain regions of strongest connectivity?

*            Which brain regions pose disease epicenters, i.e., regions where atrophy and connectivity alteration coincide?

*            What is the longitudinal spreading pattern of vascular pathology in the human connectome?

*            How do imaging markers of brain network characteristics contribute to predicting vascular cognitive impairment, adjusted for demographic factors and selected blood biomarkers?

We propose to expand our investigation by exploring the effects of CSVD on physical activity parameters, such as hand grip strength and accelerometry data, which are vital metrics for assessing late-life functionality. This extended analysis aims to ascertain:

*            The correlation between small vessel disease markers and physical activity and motor function measures in the general population.

*            The potential covariation of CSVD effects on motor and cognitive function, indicating a simultaneous physiocognitive decline.

Additionally, we plan to examine CSVD-related changes in individuals at a familial risk of dementia. To this end, we request access to data regarding familial International Classification of Diseases (ICD) diagnoses. This supplementary data will facilitate answers to:

*            Whether individuals at familial risk of dementia significantly differ from the population norm concerning CSVD-related cortical and subcortical tissue microstructure markers.

*            The possibility of classifying individuals at risk of dementia based on these markers, thus highlighting their predictive potential.

Lastly, we aim to include access to data concerning atrial fibrillation, a potential determinant of small vessel pathology, which would encompass ICD diagnoses and associated diagnosis dates. This added data would enable us to address:

*            Whether individuals with atrial fibrillation show more severe markers of cerebral small vessel disease, including tissue integrity indices derived from anatomical and diffusion-weighted MRI, White Matter Hyperintensities (WMH) burden, and peak-width of skeletonized mean diffusivity.

*            The relationship between atrial fibrillation, CSVD and cognitive performance.