PBC Predict: Prediction models and predictive biomarkers for primary biliary cholangitis

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Primary biliary cholangitis (PBC) is an autoimmune liver disease in which the body's own immune system causes damage to the small bile ducts inside the liver, eventually leading to cirrhosis (scarring of the liver). Current guidelines on the management of PBC recommend a 'step-up' approach to treatment, meaning that all patients start treatment with a medication called ursodeoxycholic acid (UDCA), which is only moderately effective but has few side effects. If the disease does not settle on UDCA alone, medication is added that is more effective - but also more likely to cause side effects. The obvious problem with this approach is that patients who need more effective treatment (i.e. those with more aggressive disease) end up waiting longer to receive it. On the other hand, 'step-down' treatment, in which everyone starts with more effective medication, would cause many patients to have unnecessary exposure to side effects. In many patients with PBC, the disease is not controlled by any of the medications that are currently available. These patients have increased risk of developing cirrhosis and needing a liver transplant. PBC is therefore a major cause of death related to liver disease, and one of the main reasons for having a liver transplant in the UK. Thus, new medications are needed for patients who do not respond to currently available medications - and accurate methods (e.g. new blood tests) are needed to predict, at the earliest possible stage, which patient will need more effective medication, and which medication will work best in that patient. This is the essence of precision medicine: to give the right medication to the right patient at the right time. UK-PBC is an ambitious collaboration between Universities, Drug Companies and the NHS to develop precision medicine for PBC. It was started with funding from the Medical Research Council (MRC). As part of UK-PBC, my team established the UK-PBC Research Cohort ('Cohort'), which already consists of more than 6,000 patients with PBC, each providing a DNA sample and consenting for clinical information to be collected from any NHS organisation. We have previously used clinical information about patients in the Cohort to develop statistical models that predict response to first-line treatment with UDCA, or future need for liver transplantation. We have used genetic information about the Cohort for large-scale genetic studies that have highlighted drugs, currently used for treatment of other autoimmune conditions, that might also work in PBC. In the proposed project, building on our previous success, we will expand the Cohort to more than 10,000 patients with PBC. We will collect large amounts of clinical information about these patients from a range of NHS organisations. We will use this clinical information to improve the accuracy of statistical models that predict response to treatment or future need for liver transplantation, which may then be used in clinical practice to tailor the treatment of PBC patients. We will combine clinical and genetic information to identify the genetic factors that determine response to treatment or future need for liver transplantation, and develop statistical models incorporating clinical and genetic information. We will measure gene regulation and gene expression in blood-based immune cells from a carefully selected group of newly diagnosed patients, and use these measurements to develop new blood tests that predict, at the earliest possible stage, which patients will need more effective medication. Finally, we will combine clinical and genetic information with measurements of gene regulation and gene expression to pinpoint the genes involved in causing PBC, which will help us to identify new medications that might work in this condition.