Identifying causal pathways in cerebral small vessel disease
Lead Research Organisation:
Imperial College London
Department Name: Brain Sciences
Abstract
Cerebral small vessel disease is the most common cause of neurological disability, seen on MRI scans as damage to the deep regions of the brain in over half of people by 65 years old. It causes 30% of strokes, falls, frailty, late-onset depression and up to 40% of dementia. However, it has no treatment due to limited understanding of the underlying mechanisms of the disease.
Small vessel disease is strongly related to long-standing high blood pressure and to its effects on the body, including stiffer blood vessels and an increased variation in blood pressure during and between each heart beat. It is also related to reduced responsiveness of blood vessels in the brain, limiting their ability to compensate for blood pressure changes. Finally, genetic studies support the role of blood pressure but also identified genes responsible for the integrity of the tissue of the brain. As such, some patients may have more severe disease because their brains are more vulnerable to being damaged.
We propose that small vessel disease is due to a balance between increased transmission of variable blood pressure to the brain, a reduced ability of the brain to compensate for this and an increased vulnerability of the brain to being damaged. However, no study has measured all these elements together in a large enough population to test this, and thus to identify and test potential treatments.
This project will combine our groups' expertise to measure all aspects of this mechanism in UK Biobank. This study includes brain scans in more than 100,000 people, detailed medical history and lifestyle information and genetic testing. However, it has lacked measurement of changes in blood flow to the brain and its ability to compensate. By adapting the brain scans in UK Biobank, we have developed novel measures of variation in blood flow to the brain with each heart beat and the ability of the lining of the blood vessels in the brain to control blood flow, measured by spontaneous fluctuations in blood flow and blood flow responses whilst performing a visual task.
The first part of this project will improve these measurements of control of blood flow to the brain. It will improve how specific they are to blood flow control rather than changes in cognitive function, focus on specific brain regions and will add direct tests of how fluctuations within blood vessels are transmitted to blood flow within the brain.
Secondly, we will work with our collaborators to refine genetic measures of tissue vulnerability, including both single genes associated with vulnerability of the brain to injury and combined scores reflecting many genes to produce an overall estimate of an individual's vulnerability to injury, independently of genes affecting blood pressure.
We will combine these new, unique measures with extensive medical history and lifestyle data, imaging measures of injury to the brain and resulting effects on cognitive function, risk of stroke and risk of dementia.
This will allow us to screen >1000 risk factors for their effects on control of blood flow to the brain, and compare them with the same relationships with damage to the brain, stroke and dementia. We will use advanced statistics to test our proposed mechanism in a single mathematical model of this pathway. This will assess whether real data is more consistent with the hypothesised mechanism causing the disease, compared to alternative theories. Finally, we will use this model to identify new factors that affect this mechanism, particularly whether medications commonly used for other illnesses may improve the pathway, thus identifying potential new treatments to be tested in future studies.
Overall, we will be able to test our hypothesised mechanism of small vessel disease within a single large population, improving our understanding of the cause of the disease, identifying new potential treatments and assessing their potential for testing in clinical trials.
Small vessel disease is strongly related to long-standing high blood pressure and to its effects on the body, including stiffer blood vessels and an increased variation in blood pressure during and between each heart beat. It is also related to reduced responsiveness of blood vessels in the brain, limiting their ability to compensate for blood pressure changes. Finally, genetic studies support the role of blood pressure but also identified genes responsible for the integrity of the tissue of the brain. As such, some patients may have more severe disease because their brains are more vulnerable to being damaged.
We propose that small vessel disease is due to a balance between increased transmission of variable blood pressure to the brain, a reduced ability of the brain to compensate for this and an increased vulnerability of the brain to being damaged. However, no study has measured all these elements together in a large enough population to test this, and thus to identify and test potential treatments.
This project will combine our groups' expertise to measure all aspects of this mechanism in UK Biobank. This study includes brain scans in more than 100,000 people, detailed medical history and lifestyle information and genetic testing. However, it has lacked measurement of changes in blood flow to the brain and its ability to compensate. By adapting the brain scans in UK Biobank, we have developed novel measures of variation in blood flow to the brain with each heart beat and the ability of the lining of the blood vessels in the brain to control blood flow, measured by spontaneous fluctuations in blood flow and blood flow responses whilst performing a visual task.
The first part of this project will improve these measurements of control of blood flow to the brain. It will improve how specific they are to blood flow control rather than changes in cognitive function, focus on specific brain regions and will add direct tests of how fluctuations within blood vessels are transmitted to blood flow within the brain.
Secondly, we will work with our collaborators to refine genetic measures of tissue vulnerability, including both single genes associated with vulnerability of the brain to injury and combined scores reflecting many genes to produce an overall estimate of an individual's vulnerability to injury, independently of genes affecting blood pressure.
We will combine these new, unique measures with extensive medical history and lifestyle data, imaging measures of injury to the brain and resulting effects on cognitive function, risk of stroke and risk of dementia.
This will allow us to screen >1000 risk factors for their effects on control of blood flow to the brain, and compare them with the same relationships with damage to the brain, stroke and dementia. We will use advanced statistics to test our proposed mechanism in a single mathematical model of this pathway. This will assess whether real data is more consistent with the hypothesised mechanism causing the disease, compared to alternative theories. Finally, we will use this model to identify new factors that affect this mechanism, particularly whether medications commonly used for other illnesses may improve the pathway, thus identifying potential new treatments to be tested in future studies.
Overall, we will be able to test our hypothesised mechanism of small vessel disease within a single large population, improving our understanding of the cause of the disease, identifying new potential treatments and assessing their potential for testing in clinical trials.
Technical Summary
Cerebral small vessel disease (cSVD) underlies up to 30% of strokes, falls, refractory depression, frailty, multimorbidity and 40% of dementia but has no specific treatment. cSVD is associated with long-standing hypertension, arterial stiffness, cerebral pulsatility, and impaired cerebrovascular reactivity, whilst genetic studies additionally identify a role for tissue vulnerability to injury. We hypothesise that cSVD is due to a balance between increased transmission of hypertension-associated haemodynamic dysfunction to the brain, impaired cerebrovascular compensation and increased tissue vulnerability.
We will firstly develop our novel measures of cerebral pulsatility and endothelial dysfunction in up to 100,000 MRI brain scans in UK Biobank, utilising the high temporal resolution BOLD imaging to measure pulsatility within a heart beat, tissue- and frequency-specific low frequency oscillations to assess transmission to the brain and local autonomic control of blood flow, and response to a visual task as an index of cerebrovascular reactivity to a stimulus.
Secondly, we will define indices of tissue vulnerability to injury from both MRI indices of microstructural injury, monogenic genetic variants associated with cSVD and a polygenic index of tissue vulnerability from cSVD associated genes, not associated with hypertension.
To test the hypothesised mechanism, we will screen >1000 clinical and demographic risk factors in UK Biobank for consistent univariate associations with both these novel measures and imaging markers of cSVD (white matter hyperintensities, DTI-indices), cognitive outcomes and algorithmically-defined clinical outcomes. We will then use structural equation modelling with latent variables for vascular aging, cerebrovascular dysfunction, tissue vulnerability, structural damage and clinical outcomes, to test the validity of this causative mechanism and provide a model to screen for potential repurposable drugs used in other conditions.
We will firstly develop our novel measures of cerebral pulsatility and endothelial dysfunction in up to 100,000 MRI brain scans in UK Biobank, utilising the high temporal resolution BOLD imaging to measure pulsatility within a heart beat, tissue- and frequency-specific low frequency oscillations to assess transmission to the brain and local autonomic control of blood flow, and response to a visual task as an index of cerebrovascular reactivity to a stimulus.
Secondly, we will define indices of tissue vulnerability to injury from both MRI indices of microstructural injury, monogenic genetic variants associated with cSVD and a polygenic index of tissue vulnerability from cSVD associated genes, not associated with hypertension.
To test the hypothesised mechanism, we will screen >1000 clinical and demographic risk factors in UK Biobank for consistent univariate associations with both these novel measures and imaging markers of cSVD (white matter hyperintensities, DTI-indices), cognitive outcomes and algorithmically-defined clinical outcomes. We will then use structural equation modelling with latent variables for vascular aging, cerebrovascular dysfunction, tissue vulnerability, structural damage and clinical outcomes, to test the validity of this causative mechanism and provide a model to screen for potential repurposable drugs used in other conditions.