Identifying biomarkers for treatment response and disease prognosis

The aim of this project is to identify biomarkers that could help us predict how patients would respond to a type of treatment called immunotherapy. Immunotherapy uses the body’s own immune system to prevent, control or eliminate disease.

Research suggests that low-grade inflammation could impact the development and ongoing symptoms of depression. Inflammation develops when part of the immune system is overactive. This overactivity can be measured by testing a patient’s blood for certain biomarkers. Biomarkers are found in blood, other body fluids or tissues. They can be a sign of existing disease or a warning that somebody will develop a disease in the future.

It is possible that some patients with depression might benefit from immunotherapy, but we know that it is unlikely to be useful for all patients with depression. This is why we need to identify biomarkers associated with how a patient responds to immunotherapy. Finding these would help us predict which patients would benefit from treatment and inform how future studies are designed.

To achieve this goal, we will look at existing data and blood samples from clinical trials of immunotherapy and cohort studies, including the Insight study. This study investigated whether reducing inflammation with an anti-inflammatory drug (tocilizumab) could help reduce symptoms of depression. This project will help us to identify potential biomarkers associated with a patient’s response to treatment and future illness course.

This project is led by Professor Golam Khandaker, Dr Paul Yousefi and Holly Fraser.