The role of vasculature in Alzheimer's disease

The role of vasculature in Alzheimer's disease and other neurodegenerative diseases is poorly understood. In spite of the myriad hypotheses relating cerebrovascular pathologies (including cerebral amyloid angiopathy and cerebral small vessel disease) to neurodegeneration, no clear consensus has emerged regarding the effect of amyloid-beta and hyperphosphorylated tau on cerebral autoregulation and the blood-brain barrier, and vice versa. In particular, these biological questions have not, to date, been investigated with the help of mathematical models. This project will investigate questions such as these by the design and analysis of mathematical models on the scale of the brain, coupling the dynamics of toxic protein spread and of cerebrovascular degeneration. This project falls within the EPSRC Mathematical Biology, Numerical Analysis, Mathematical Analysis, and Nonlinear Analysis research areas. This project will be conducted in collaboration with Hoffmann-La Roche. An initial goal of the project is to model and simulate the fall in cerebral blood flow across the different regions of the brain based on the presence of toxic proteins, such as tau. Models have been developed by others that can simulate the temporal evolution of the spatial distribution of toxic protein mass across the brain. One such model (developed by the Goriely group and collaborators) employs a reaction-diffusion partial differential equation to describe the evolution of the protein mass distribution over the brain (a continuum approach). A similar model partitions the brain into discrete, disjoint regions and seeks the protein mass at each region with respect to time by posing a coupled ordinary differential equation problem. It is this latter model that we aim to expand to include vascular information. Given a graph representation of a vascular network in a small brain region, one can solve a linear system for the steady-state flows along each edge of the graph (and the total flow through the network). When edges are removed from the graph or when their resistance to flow is increased (like vessels being occluded or narrowed), the flow through the network decreases. We want to simulate this process over time, where the probability of vessel occlusion increases with increased protein mass in the given brain region. The next step will be to interrogate the biological literature for hypotheses regarding the effect of reduced blood flow or increased vascular damage on the accumulation and clearance of Abeta and tau, with the goal of coupling the vascular model just described back to the protein spread model (e.g. reduced blood flow might lead to a decrease in Abeta clearance). The relationship between cerebrobvascular pathologies and neurodegeneration is a question of great complexity and interest. Given the nascent nature of this subfield of neurodegeneration and the fact that mathematical models have not yet been used to make predictions and test biological hypotheses, this project will involve highly original research and will have great potential to produce impactful scientific results.

The UK's world-leading position in biomedical research is critically dependent upon training scientists with the cutting-edge research skills and technological know-how needed to drive future scientific advances. Since 2009, the EPSRC and MRC CDT in Systems Approaches to Biomedical Science (SABS) has been working with its consortium of 22 industrial and institutional partners to meet this training need.

Over this period, our partners have identified a growing training need caused by the increasing reliance on computational approaches and research software. The new EPSRC CDT in Sustainable Approaches to Biomedical Science: Responsible and Reproducible Research - SABS:R^3 will address this need. By embedding a sustainable approach to software and computational model development into all aspects of the existing SABS training programme, we aim to foster a culture change in how the computational tools and research software that now underpin much of biomedical research are developed, and hence how quantitative and predictive translational biomedical research is undertaken.

As with all CDT Programmes, the future impact of SABS:R^3 will be through its alumni, and by the culture change that its training engenders. By these measures, our existing SABS CDT is already proving remarkably successful. Our alumni have gone on to a wide range of successful careers, 21 in academic research, 19 in industry (including 5 in SABS partner companies) and the other 10 working in organisations from the Office of National Statistics to the EPSRC. SABS' unique Open Innovation framework has facilitated new company connections and a high level of operational freedom, facilitating 14 multi-company, pre-competitive, collaborative doctoral research projects between 11 companies, each focused on a SABS student.

The impact of sustainable and open computational approaches on biomedical research is clear from existing SABS' student projects. Examples include SAbDab which resulted from the first-ever co-sponsored doctorate in SABS, by UCB and Roche. It was released as open source software, is embedded in the pipelines of several pharmaceutical companies (including UCB, Medimmune, GSK, and Lonza) and has resulted in 13 papers. The SABS student who developed SAbDab was initially seconded to MedImmune, sponsored by EPSRC IAA funding; he went on to work at Roche, and is now at BenevolentAI. Similarly, PanDDA, multi-dataset X-ray crystallographic software to detect ligand-bound states in protein complexes is in CCP4 and is an integral part of Diamond Light Source's XChem Pipeline. The SABS student who developed PanDDA was awarded an EMBO Fellowship.

Future SABS:R^3 students will undertake research supported by both our industrial partners and academic supervisors. These supervisors have a strong track record of high impact research through the release of open source software, computational tools, and databases, and through commercialisation and licensing of their research. All of this research has been undertaken in collaboration with industrial partners, with many examples of these tools now in routine use within partner companies.

The newly focused SABS:R^3 will permit new industrial collaborations. Six new partners have joined the consortium to support this new bid, ranging from major multinationals (e.g. Unilever) to SMEs (e.g. Lhasa). SABS:R^3 will continue to make all of its research and teaching resources publicly available and will continue to help to create other centres with similar aims. To promote a wider cultural change, the SABS:R^3 will also engage with the academic publishing industry (Elsevier, OUP, and Taylor & Francis). We will explore novel ways of disseminating the outputs of computational biomedical research, to engender trust in the released tools and software, facilitate more uptake and re-use.