Exploiting methodological and technological innovations for targeted treatment and precision medicine

Rheumatoid arthritis (RA) is an autoimmune disease in which the body’s immune system mistakenly attacks its own tissues inside the joints. This causes inflammation and pain. Over time, it can lead to irreversible joint damage and disability. Early effective treatment can offer substantial long-term benefits to those affected, but diagnosing the disease early can be difficult. Similarly, treatments are not always effective, and we cannot reliably predict what drugs will work for each patient. If we could identify genes that cause RA, we could develop drugs targeting the proteins that these genes produce. We could also predict response to drugs based on measuring the activity of these genes. To this end researchers over the last 20 years have studied genetic variation, that is differences in people’s DNA, in tens of thousands of people with and without RA. These studies focus on local (“cis-”) effects of variants on nearby genes. While often related to inflammation, genes identified by this approach are mostly not specifically relevant to RA and cannot be easily targeted by drugs. The aim of this project is to exploit a new method of genetic analysis (Genome-wide Aggregation of Trans-Effects, or GATE). This method identifies core genes for disease by focusing on the long-range (“trans-”) effects of variants far away in the genome. The method is motivated by a recent theory in genetics called the “omnigenic hypothesis”. It says that while most common genetic variants might have a tiny effect on disease, these effects come together on a small number of core genes via trans-effects on the activity of these genes. We have developed this method and applied it to several autoimmune diseases. For RA, this identifies up to fourteen core genes. Seven of these produce immune checkpoint proteins, including the protein PD-1. Cancer cells exploit these proteins to evade the body’s immune system. Drugs that target these proteins, to stop them from activating the immune system, are now being developed: a drug that targets PD-1 has shown encouraging results in an early trial of RA. The specific objectives of this project are: To develop further the identification of core genes for RA and other autoimmune diseases through GATE analysis. This will use advanced statistical and computational methods, and new data on proteins and gene activity that will soon be available from UK Biobank, a large health study of over 500,000 people in the UK. To learn how to use the proteins produced by these core genes to predict who might develop RA among those with early symptoms, and how well one might respond to a treatment, based on their protein profile. A custom panel of proteins will be defined and measured in stored blood samples from existing cohorts available through collaborators. The expected outcome of this work will be to speed up the development of more effective drugs for RA, and to find protein profiles that tell apart people with early RA from those without it. Protein profiles will also provide a rational basis for choosing treatment.