Personalised medicine in pulmonary fibrosis

Pulmonary fibrosis (PF) is a devastating disease where the lungs become scarred making it difficult to breathe. One half of individuals die within 3-5 years of diagnosis. Around 6,000 people are diagnosed with idiopathic pulmonary fibrosis (IPF, the most common form of PF) in the UK each year but this number is rising. In 2022, 1.2% of deaths in England and Wales (6,805 in total) were due to IPF (https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/deathsregistrationsummarytables/2022). Current drugs do not offer a cure and it is thought that around half of individuals stop taking treatment either due to lack of effect on disease progression or due to debilitating side-effects. By comparing the genetics of individuals with PF to those without PF, I have previously shown five biological processes that drive the risk of the disease: how cells age, how cells make copies of themselves, the way scar tissue forms, how the lungs defend themselves and how well cells stick together. I have also shown that scar tissue regulation is important in terms of how quickly PF progresses. Understanding the underlying biological processes that drive the disease is critical to understanding the disease, helps develop new treatments and can identify groups of individuals who may respond better to certain treatments. We propose a project combining expertise in genetics, statistics and biological sciences working with a patient advisory group to: Develop new effective treatments for PF Identify which treatments should be given to which individuals Firstly, we will investigate whether an individual’s genetics makes them more likely to respond to current treatments, to develop side-effects or to have specific symptoms. We will compare symptoms in people affected by PF to the general population to identify whether symptoms in PF need specific treatments (for example, should we treat cough in individuals with PF the same way we treat cough in the general population). Secondly, we will identify parts of the DNA that affect i) how quickly the disease progresses, ii) how long individuals live after diagnosis and iii) the biological pattern of PF seen on a CT scan. This will help develop new treatments. We will compare the genetics of PF to other diseases, particularly fibrotic diseases affecting other organs. Many of these diseases have available treatments and if we identify diseases with a shared genetic make-up with PF, we may be able to use these drugs for PF. Thirdly, we will directly test how genetic changes affect treatment response in human cells and tissues. We will do this by “knocking down” genes of interest to see how the cells behave and how human tissue responds to different drugs. Finally, we will combine all the information we have gathered and build a computer-based model to help clinicians chose the right treatment for an individual patient. Using the patient’s clinical and genetic information, the computer model will predict how the disease will likely progress over time if the individual was given different treatments. From this the patient and clinician will be able to choose which treatment to take to slow down the progression of the disease while reducing treatment side-effects and disease symptoms. To maximise the clinical utility of these models, ways of presenting these models will be co-developed with clinical and patient partners. Together this approach will move us towards developing desperately needed targeted and effective treatments for PF.