Lead Research Organisation: University of Cambridge
Department Name: Cambridge Institute for Medical Research


Between 5 and 10% of the population will develop an autoimmune or inflammatory disease at some point during their lifetime. These diseases behave differently from person to person, with some people having an aggressive course while others have a more benign disease. When such diseases develop doctors need to treat them "blind" - as they have no way of predicting which patients have naturally benign disease, requiring only minimal treatment, and those who will require more intensive treatment to obtain control. This is a major problem for patients and for the healthcare system. It means that patients who need intensive therapy often find that this needs to be delayed until their disease progresses and the need for such therapy becomes obvious. Conversely, the early indiscriminate use of treatment for these diseases may mean that those who would do well without such treatment receive it unnecessarily, exposing them to significant side-effects. Such poorly targeted use of treatments also wastes limited NHS resources.

We will use cutting-edge "genomic" technology to measure the genes expressed in blood white cells in patients with a number of diseases before and after treatment. Analysing this gene expression data using advanced computational techniques will allow us to identify subsets of patients that would not be apparent using conventional clinical assessment, and to determine if these subsets are associated with different disease outcomes. Additional tests which can be developed based on these observations might allow early diagnosis of patients with rare diseases, or be used to measure the degree of disease activity. We have proven that such an approach works, having recently discovered a biomarker that predicts outcome in four different conditions, including inflammatory bowel disease (Crohn's disease and ulcerative colitis), lupus and vasculitis - this is now entering clinical trials.

The proposed programme will complete the analysis of a large study established in these four patient groups over the last ten years, and continue and extend the study over the next five years, allowing the use of recent advances in technology and the inclusion of additional diseases, such as AIH, EGPA/Churg Strauss and multiple sclerosis.

Technical Summary

Autoimmune and inflammatory diseases are chronic, relapsing remitting conditions affecting up to 10% of the population, a figure that is rising rapidly in both the developed and developing worlds. These diseases are often difficult to definitively diagnose and follow very variable courses, with some patients following an aggressive course while others follow a more benign course. Early diagnosis and the ability to predict likely course will be key to the introduction of treatments tailored to the individual patient and therefore likely to be more efficacious. Using transcriptional analysis of purified leukocyte subsets we have begun to uncover gene signatures with such diagnostic and predictive utility in several immune-mediated diseases. We will complete the analysis of samples generated over the last ten years and in addition to extend these analyses into new diseases and additional cell types.
For these new studies we will use high-throughput, multi-chromatic, fluorescence activated cell sorting to isolate rarer populations of cells at high purity and with sufficient yield to allow downstream analyses. We will also move away from microarray-based measurements of cellular transcriptomes to the use of next generation sequencing-based RNA-Seq, which will be cost-effective and provide a more comprehensive view of both the mRNA and MiRNA transcriptomes. In addition to these cell population level transcriptomic analyses we will also perform cutting edge single cell transcriptomics to examine the heterogeneity of specific populations. Finally, we will reanalyse existing and novel genome-wide association datasets stratified by clinical outcome to identify novel genetic variants associated, not with disease prevalence, but with disease prognosis. It is anticipated that the integrated analysis of these genomic and genetic data with detailed clinical data using existing and novel software tools will lead to the identification of useful novel biomarkers

Planned Impact

The biomarkers sought in this comprehensive analysis will benefit patients, the NHS, and the pharmaceutical industry. As an example of such benefits I will focus on the biomarker which has already been identified, as this will be studied further in the proposed programme, and it is expected that similar prognostic biomarkers will also be discovered in these and other diseases. The impact of this specific biomarker, which predicts long-term outcome at presentation in patients with active disease, is outlined below.

The CD8 T cell biomarker divides patients with AAV, SLE, Crohn's disease and ulcerative colitis, into two distinct groups. One group, comprising approximately a third of patients, has a 90% chance of disease relapse or progression within two years of diagnosis, whereas the other group has around a 20% chance of such relapse. This knowledge should allow us to focus intensive therapy on the third who will do badly, optimising their chances of recovering from illness, and will allow us to reduce or minimise treatment in the two thirds predicted to do well, which will reduce unnecessary treatment side effects.

Prognostic biomarkers will be of great benefit to the NHS - they will allow the focussing of expensive therapeutic resources on those who need them most, which will reduce unnecessary drug costs and, by using these treatments early in the course of disease rather than waiting for progression, will reduce morbidity and thus the costs of admissions and additional investigations and treatment.

The Pharmaceutical Industry
The ability to identify patient subgroups at high risk of disease progression or relapse should allow the refinement of clinical trials - focussing on those patients with a high probability of disease response will reduce the number of patients that need to be included in these expensive Phase III studies, and is also likely to allow an earlier readout of drug efficacy. This will be of enormous benefit to the pharmaceutical industry, as the cost of Phase III studies presents a major obstacle to drug development, and prognostic biomarkers of the sort we have discovered may reduce costs by a factor of four. In addition to these prognostic biomarkers, other biomarkers may allow monitoring of disease activity, or improved early diagnosis of complex autoimmune and inflammatory illnesses, and will also have significant patient benefits, and knock-on effects in reducing costs and increasing efficacy within the NHS and pharmaceutical industry.
Description Wellcome Trust Investigator Award
Amount £1,600,000 (GBP)
Funding ID 200871/Z/16/Z 
Organisation The Wellcome Trust Ltd 
Department Wellcome Trust Senior Investigator Award
Sector Private
Country United Kingdom of Great Britain & Northern Ireland (UK)
Start 08/2016 
End 07/2021