Defining and diagnosing neurodegenerative Movement Disorders through integrated analysis of Genetics And neuroPathology (MD-GAP)

We are entering an era in which therapies for degenerative diseases such as Parkinson's and Alzheimer's will be directed towards the underlying protein pathology. Most progressive later onset neurological diseases involve the deposition of abnormal insoluble proteins as aggregates, for example Lewy bodies in Parkinson's and amyloid plaques in Alzheimer's. There are now an increasing number of experimental therapies which are directed towards protein pathology, for example involving antibodies and gene based therapies. Genetics has provided tremendous insights into neurological disease, largely based on studies in clinically diagnosed patients. Neuropathology is the "gold standard" for the diagnosis of neurological diseases, and the MRC and UK charities have invested in developing the MRC UK Brain Banks Network (BBN) to enable better understanding of these conditions.
Here, we will integrate high throughput genetic analysis with neuropathology to improve the diagnosis and understanding of neurological disease.

Early diagnosis: is a major barrier to the delivery of effective treatment. At the earliest disease stages typical disease features may not be apparent. For example, slowness of movement (Parkinsonism) can be due to multiple different diseases including Parkinson's disease, and a definite diagnosis may not become apparent until the clinical course and response to treatment are established. We will study genetic variant data from pathologically diagnosed cases to improve early diagnosis. We believe that diagnostic algorithms based on analyzing many genetic markers (polygenic risk) will improve the clinical diagnosis.

Improved case-control analysis: will be achieved by comparing individuals with pathologically proven diseases such as Parkinson's with controls unaffected by neurological disease. This will remove the effect of clinical misdiagnosis in the analysis of neurological disease.

Disease heterogeneity: is an important feature of conditions such as Parkinson's. Some patients develop dementia and rapidly progressive disease whereas others have a more benign, milder disease course. We believe that this heterogeneity is driven by differential neuropathology. For example, dementia in Parkinson's is associated with Alzheimer's co-pathology (amyloid plaques and neurofibrillary tangles). We will directly study the genetic drivers of co-pathology and integrate this with analyses of clinical heterogeneity to decode the different patterns of neurological disease, which may ultimately respond to different therapies.

Improving resources: The BBN is used by researchers into neurological disease from around the world. There is a growing need to understand the implications of genetic risk factors - and one of the most straightforward ways to do this is to look at brain tissue from individuals with and without the genetic risk factor. This genetic data will be made available to bona fide researchers which will speed up this process and allow researchers to select tissue and samples of interest, maximising the usefulness of these patient tissue archives.

The integration of genetics with imaging has led to major insights into brain development and neurodevelopmental disorders. Late onset neurodegenerative disorders are associated with abnormal protein aggregates which define and drive the disease, and so integration with neuropathology is the logical approach to these conditions.
We will obtain DNA from ~ 2500 individuals with pathologically defined neurodegenerative movement disorders and ~ 1000 controls. In collaboration with the MRC UK Brain Banks Network (BBN) we will collate initial clinical diagnosis, pathological diagnosis, age at onset, gender and survival. We will collate Braak and Thal pathological stage data reflecting the extent of three major neurodegenerative disease pathologies - tau, alpha-synuclein and amyloid. In a subset of 750 Lewy body disorder spectrum cases we will use digital pathology approaches to quantify the amyloid, tau and alpha-synuclein burden in three important representative areas: frontal cortex, entorhinal cortex and cingulate gyrus. We will genotype each case and control using the Illumina MegaEX / Neurochip v3 single nucleotide variant array. This will provide information on genome wide common variation in individuals with different ancestries; risk variants from genome wide association studies (GWAS) and neurodegenerative rare variants. We will define the genetic drivers of pathology based on candidate gene/transcript analysis, and with hypothesis free GWAS. We will correlate genetic data with clinical data including survival, rate of progression and dementia. We will carry out pathologically defined genome wide association studies, which will be meta-analysed with pathologically defined GWAS from around the world, and use the data to develop polygenic risk tools to enhance diagnostic accuracy. Genetic data will be made available via the BBN database to enable future exploration of the downstream effects of genetic variation by bona fide investigators.

Who will benefit from this research?
This project will benefit patients, clinicians, researchers and the pharmaceutical industry. It will also assist the development of the MRC UK Brain Bank Network.

How will they benefit from this research?
Patients and clinicians will benefit from improved clinical diagnosis and understanding of disease heterogeneity.
Researchers will benefit from this research through the direct definition of the drivers of neurodegeneration which will provide new targets for functional biology research and the development of new therapeutic strategies.
Researchers will also benefit from the availability of genetically well characterised tissue from the UKBBN which can be used for many downstream projects.
The pharmaceutical industry will benefit from improved diagnosis, the identification of new drug targets and the availability of well characterised tissue for the development of therapies and imaging ligands.