Uveitis is an umbrella term for immune mediated intraocular inflammation and affects the specialised light sensing cells that comprise the retina. Most cases of non-infectious Uveitis are linked to changes in the behaviour of the immune system (the body’s defence against illness and infection), which becomes overactive and mistakenly attacks the eye, leading to retinal damage. This type of immune-mediated inflammation accounts for a significant prevalence of visual loss in both children and adults.

Imaging of uveitis patients reveals a diverse array of disease patterns, some areas of an individual’s retina showing signs of disease but other sites appearing unaffected. Evidence from other immune-mediated diseases in other organs suggests such inflammation is caused by only a small fraction of infiltrating immune cells. Therefore, better understanding is needed as to where these cells are located in the retina, and how they interact with other cells at sites of tissue inflammation.

In a NERC-funded PhD, the team at University of Bristol have recently established a novel technique that enables us to isolate small numbers of defined immune cell populations from the whole retina, to assess the cellular transcriptome (the global profile of genes expressed). This work has highlighted how different sets of genes are altered in different types of cell during inflammation. However, this whole tissue approach does not allow us to distinguish the regional differences, inflammatory vs normal areas, that are seen clinically across the retina. 

During this project, Dr David Copland and his team at University of Bristol will refine their approach by combining clinical imaging to first identify, and then biopsy specific regions of active inflammation from across a single retina to understand the differences in gene expression.

The aim of this study is to generate for the first time a comprehensive assessment of molecular disease pathways (endophenotype) that are expressed by specific populations of immune cells found in the retina, and how these influence the distinct disease patterns (pathotype). The data will feed major programme funding, which ultimately allows us to move toward understanding at a single-cell level, how cells interact with each other and the tissue. The findings will inform other research areas in their lab, most notably the optimisation and development of novel targets for the next-generation of therapeutics.

Read more about uveitis here.

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