Cellular-resolution in situ transcriptomics of the mouse brain and Alzheimer's disease models

The brain is composed of hundreds of subtly-different cell types, spread over hundreds of distinct regions. The sensory, motor, and cognitive functions the brain produces, arise from circuits distributed globally across these regions. To understand brain function, it is therefore essential to understand the global spatial organization of its component cell types. Similarly, to understand how cognition can falter in disease conditions, it is essential to understand how pathologies affect circuits across the whole brain.

Alzheimer's disease is a devastating disorder of brain function, with a tremendous and still growing social and economic cost. Although much research has focused on a small set of regions (the hippocampus and entorhinal cortex), Alzheimer's disease affects the whole brain. For example, drugs targeting a small but very specific circuit, the basal forebrain cholinergic system, are amongst the few treatments approved for relief of Alzheimer's symptoms. Many other specific brain regions are likely to be involved also, but an understanding of the brain-wide pathology of the disease is currently lacking. Each brain region contains many finely-distinguished subtypes of neurons, as well as other cell types such as microglia, astrocytes, oligodendrocytes, and vascular cells, which all likely play a role in the disease aetiology. Precious little information is available on how these fine subtypes are involved in the disease.

This project will employ a new technology, called in situ transcriptomics, to understand the global structure of the brain, and it is disrupted by the pathologies underlying Alzheimer's disease, using mouse models. This technology can localize the expression of many genes simultaneously, to sub-micrometer resolution, in samples of any tissue from any species. Because different cell types express different combinatorial patterns of genes, parallel measurement of a cell's gene expression profiles allows fine cell type classification. Furthermore, because changes in cellular function are almost always reflected in changes in gene expression, applying the technology to disease models will allow scientists to understand how the function of each cell type changes under pathological conditions.

The technology is still under development, and is currently found in only a few labs worldwide. Our group at UCL are one of the developers of the technology. We have recently developed it to a point where it can localize up to 1000 genes simultaneously at high efficiency, and automated it so that it can run at high enough throughput to process an entire mouse brain. We propose here to apply this newly-established technology at scale, to produce an entire atlas of expression of 1000 carefully chosen genes, at submicron resolution, across the whole mouse brain. We will use this to spatially localize all the brain's cell types (building on work from a previous non-spatial transcriptomic technology). We will then apply the same methodology to two mouse lines, that model the two main types of pathology underlying Alzheimer's disease: the APPNL-G-F amyloid model, and the THY-Tau22 model. This will enable us to see how multiple types of neuron and non-neurons across all brain regions are affected by the amyloid and tau pathologies.

All data will be made freely available, enabling scientists worldwide to use it to guide new experiments and hypotheses regarding the function of the healthy and diseased brain. This will provide foundational information, greatly accelerating progress towards understanding not only Alzheimers but also a wide range of other neurological and psychiatric disorders of cognition including for example schizophrenia, depression, bipolar disorder, frontotemporal dementia, Parkinson's disease, and Huntington's disease.

This project will employ in situ transcriptomics to understand the spatial organization of cell types throughout the mouse brain, and how this is modified in models of Alzhimer's disease.

Several methods for in situ transcriptomics are currently under development. We have recently developed a method based on padlock-probe amplification that allows hundreds of genes to be localized simultaneously at high throughput. We have developed algorithms using this data to probabilistically assign each cell to types defined by previous scRNA-seq. We have validated this approach in mouse hippocampus, confirming that it localizes fine subtypes of interneuron to their classically established spatial locations.

Improvements to the method now allow up to 1000 genes to be simultaneously localized at higher efficiency, and we have automated the method to run at high enough throughput to process an entire mouse brain. We will use this new technology to localize the expression of 1000 carefully chosen genes across the whole mouse brain, at submicron resolution. The resulting data will consist of the spatial expression profiles of these genes, across 21 sagittal sections of the mouse brain, spanning its full medio-lateral extent (the same resolution as in the Allen reference atlas). We will use this to spatially localize all cell types identified by previous whole-brain scRNA-seq. We will apply the same methodology to two mouse models of Alzheimer's disease: the APPNL-G-F model and the THY-Tau22 model. This will reveal how all cell types (neuronal and other), in all brain regions, are affected by the amyloid and tau pathologies.

The proposal will have three main pathways to impact. First, by contributing key data to understanding of the biological processes underpinning Alzheimer's disease, this project will help the scientific community bring forward the day that the devastating social and economic costs of this disease can be ameliorated. Second, the foundational data we will produce on the wild-type brain will have impact on research toward treating a much larger number of neurological and psychiatric diseases. Third, our application of a transformative new technology at large scale will help establish this technology in the UK, with benefits to all fields of biomedical research, as well as future potential in diagnostics.

Alzheimer's disease is a degenerative brain disorder and the most common cause of dementia. Dementia affects 53 million people worldwide, being the 6th-leading cause of death. Statistics revealed that 10% of the population aged 65, and up to 50% of people aged >85 suffer from AD, with estimated incidence of 131.5 million patients by 2050, and worldwide costs of US$818 billion including healthcare, long-term caretaking, hospice service (World Alzheimer Report 2016). It is clear that AD represents a major public health concern, as well as a social and economic burden. Dementia not only devastates lives, but creates enormous cost to the wider economy, an estimated £26 billion a year in the UK alone, which is expected to more than double in the next 25 years, reaching £56bn by 2040 (Alzheimer's research UK). Dementia has higher health and social care costs (£11.9bn) than cancer (£5.0bn) and chronic heart disease (£2.5bn) combined, but receives a lower level of research investment.

Although the need for novel therapies is great, a deeper understanding of molecular and cellular mechanisms is required to make this possible. No new drug has been approved by the FDA since 2003, and a more detailed understanding of the complex pathology underlying this disorder is thus extremely important. The present proposal would contribute an unprecedented dataset, covering on all areas of the brain, and considering effects on hundreds of genes in all cell types.

All data collected in this study will be freely and publicly available. This will allow scientists worldwide to analyze the data, and to draw conclusions far beyond what we will be able to do in the three year period.

Beyond Alzheimer's disease, our data will provide foundational information to understand the brain's global cellular composition, which will be very useful information for a wide range of neurological and psychiatric disorders. Although the mouse brain is certainly not the same as the human, its basic organization and cell types, including fine subclasses of neurons, seems to be remarkably similar. The data we collect here will therefore accelerate progress towards understanding a wide range of disorders of cognition including for example schizophrenia, depression, and bipolar disorder. Furthermore, because different neurodegenerative conditions share at least some common pathways, our data are likely to yield information useful for the study of conditions such as frontotemporal dementia, Parkinson's disease, and Huntington's disease.

Finally, the project would constitute a flagship application for the new and very exciting technology of in situ transcriptomics. This cutting-edge technology can be used in all fields of biomedical research, providing foundational information on the organization of organs, in all species, and even in non-animal life such as plants. We have experienced very high levels of interest in this technology from colleagues in diverse fields of biomedical science, from cancer to ophthalmology. By helping develop and promote the technology, therefore, this project would accelerate progress in many different fields of biomedical research.