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 Wellcome Trust 
Department Wellcome Trust Senior Investigator Award
Sector Charity/Non Profit
Country United Kingdom
Start 07/2016 
End 07/2021
Description The application relates to methods of assessing whether an individual has an exhausted CD8+ T cell or lack of CD4+ T cell costimulation phenotype, and the use of such methods in determining an individual's risk of autoimmune disease progression, progression of a chronic infection, not responding to a treatment for a chronic infection, not mounting an effective immune response to vaccination, infection-associated immunopathology, transplant rejection, or cancer progression. The application also relates to in vitro methods for assessing whether CD8+ and CD4+ T cells in a sample have an exhausted CD8+ T cell or lack of CD4+ T cell costimulation phenotype, and for identifying a substance capable of inducing an exhausted CD8+ T cell or lack of CD4+ T cell costimulation phenotype in an individual, as well as a kit for assessing whether an individual has an exhausted CD8+ T cell or lack of CD4+ T cell costimulation phenotype or whether an exhausted CD8+ T cell or lack of CD4+ T cell costimulation phenotype is present in a sample of CD8+ and CD4+ T cells. 
IP Reference WO2016185182 
Protection Patent application published
Year Protection Granted 2016
Licensed Yes
Impact Too early
Description Patent describes a method for predicting whether patients with autoimmune disease will follow a quiescent or severe disease course. 
IP Reference EP2389582 
Protection Patent granted
Year Protection Granted 2011
Licensed Yes
Impact Too early.
Company Name Predictimmune Ltd 
Description PredictImmune is developing pioneering tools for guiding treatment options in immune-mediated inflammatory diseases with the first product addressing Inflammatory Bowel Disease (both Crohn's disease and ulcerative colitis). The test, based on a simple whole-blood quantitative PCR assay, predicts long-term disease outcome at diagnosis prior to treatment, stratifying patients into those likely to follow either a quiescent or frequently relapsing course and informing clinical management. 
Year Established 2017 
Impact Too early.
Website http://www.predictimmune.com
Description Invited Speaker - Ken Smith 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Professional Practitioners
Results and Impact Cellular and Molecular Phenotypes in Human Health and Disease, NUS, Singapore
Year(s) Of Engagement Activity 2022
Description Invited Speaker - Ken Smith 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Professional Practitioners
Results and Impact Ken Smith - "Using whole genome sequencing in sporadic immunodeficiency to understand common disease: TRAF3 and beyond".
Year(s) Of Engagement Activity 2022
Description Invited Speaker - Ken Smith SYSCID 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Invited Speaker: SYSCID, Kiel, Germany
Year(s) Of Engagement Activity 2022