Use of transcriptional signatures to understand the immunopathogenesis of the granulomatous diseases tuberculosis and sa

Lead Research Organisation: MRC National Inst for Medical Research

Abstract

Tuberculosis is a disease cause by infection with the bacteria Mycobacterium tuberculosis. It is a major public health problem, which is on the increase and infects a third of the world's population. The resurgence in the UK has led to about 8,000 new reported cases each year. The diagnosis can be difficult particularly when differentiating from the disease sarcoidosis. Both diseases can cause similar symptoms and are secondary to disorders of the immune system. Confirming the diagnosis between the diseases can require invasive procedures, but is vital as the treatment is so different. To help us improve diagnosis, treatment and prevention of TB we must understand the underlying biological mechanisms involved. A method called gene expression profiling can be used to measure the activity of genes (ie measure the genes that are 'switched on' or 'switched off') in cells. Statistical analysis of this information can be used to determine a specific signature of gene activity.

This project will use expression profiling to analyse blood from patients with TB, sarcoidosis and healthy controls. Comparing signatures between the groups will determine diagnostic tests to distinguish between the diseases and yield insights into the biological mechanisms involved, to ultimately develop better therapeutic approaches.

Technical Summary

Tuberculosis (TB) is increasing worldwide, including in the UK where approximately 8,000 new cases are reported annually. Its diagnosis can be difficult leading to delays in appropriate treatment. A significant problem is differentiating TB from sarcoidosis; both are multisystem granulomatous diseases that preferentially involve the lung and can be indistinguishable clinically without the use of invasive procedures. The underlying pathogenesis of granulomatous inflammation is poorly understood. Gene expression profiling has been successfully applied to inflammatory and infectious diseases to determine causative factors in pathogenesis and develop novel diagnostic tools. Expression profiling determines gene activity using microarray technology to measure differential gene expression. However,the size and complexity of the data makes interpretation difficult, forcing scientists to focus on a handful of candidate genes for further study, leading to criticism that such microarray studies are "fishing expeditions". Bioinformatic approaches such as statistical clustering and a recently published novel approach, based on modular transcriptional analysis, allow complex data to be presented in a more accessible form that allows the generation of a specific profile or transcriptional signature. Unpublished work from NIMR has successfully used this method to identify distinct signatures for active and latent TB.

Aims and objectives
1) Distinguish between TB and sarcoidosis using transcriptional signatures
2) Demonstrate the effect of treatment on these signatures
3) Use these signatures to improve understanding of pathogenesis
4) Identify biomarkers for diagnosis and treatment monitoring

Design and Methods.

Four cohorts will be recruited: active pulmonary TB, acute and chronic pulmonary sarcoidosis and healthy controls. Whole blood samples will be collected, before and after treatment. Microarray analysis of extracted RNA will be performed, and the transcriptional modular and clustering methods will be applied, generating signatures, that will be compared between cohorts, and longitudinally. How these signatures reflect the involvement of the effector proteins of the innate and adaptive immune response will be assessed using suspension bead immunoassay and flow cytometry.

Scientific and medical opportunities
These novel genomic and bioinformatics approaches have greatly enhanced our understanding of complex autoimmune diseases and applying them to TB and sarcoidosis will improve our understanding of the pathogenesis of granulomatous diseases. This knowledge is vital for the development of more effective therapeutic approaches.
Distinguishing between TB and sarcoidosis commonly requires invasive biopsies and even these may not be sufficient. This modular approach, by incorporating thousands of biomarkers into an easily interpretable format will improve diagnosis and allow monitoring of treatment response.
 
Description Data processing 
Organisation Baylor Scott & White Health
Department Baylor Institute for Immunology Research
Country United States 
Sector Academic/University 
PI Contribution Anne O'Garra is a long term collaborator with BIIR. They provide access to their facilities and there is a mutual exchange of intellectual input.
Collaborator Contribution Allowed use of their facilities to process the samples. Provided advise on data analysis and interpretation of results.
Impact Data from processing samples.
 
Description Recruitment of patients 
Organisation Imperial College Healthcare NHS Trust
Department Respiratory at St Mary's Hospital
Country United Kingdom 
Sector Public 
PI Contribution I recruit patients for our study from the Royal Free Hospital
Collaborator Contribution Able to recruit patients from the hospitalAble to recruit patients from the hospitalSent samples from patients they had recruited at the hospital. Discussions with clinical expert in the sarcoidosis field.Able to recruit patients from the hospital. Discussion with clinical expert in sarcoidosis.
Impact Recruitment of patients
Start Year 2009
 
Description Recruitment of patients 
Organisation Oxford University Hospitals NHS Foundation Trust
Department Department of Respiratory Medicine
Country United Kingdom 
Sector Hospitals 
PI Contribution I recruit patients for our study from the Royal Free Hospital
Collaborator Contribution Able to recruit patients from the hospitalAble to recruit patients from the hospitalSent samples from patients they had recruited at the hospital. Discussions with clinical expert in the sarcoidosis field.Able to recruit patients from the hospital. Discussion with clinical expert in sarcoidosis.
Impact Recruitment of patients
Start Year 2009
 
Description Recruitment of patients 
Organisation Royal Free Hospital
Country United Kingdom 
Sector Hospitals 
PI Contribution I recruit patients for our study from the Royal Free Hospital
Collaborator Contribution Able to recruit patients from the hospitalAble to recruit patients from the hospitalSent samples from patients they had recruited at the hospital. Discussions with clinical expert in the sarcoidosis field.Able to recruit patients from the hospital. Discussion with clinical expert in sarcoidosis.
Impact Recruitment of patients
Start Year 2009
 
Description Recruitment of patients 
Organisation Royal Free London NHS Foundation Trust
Country United Kingdom 
Sector Public 
PI Contribution I recruit patients for our study from the Royal Free Hospital
Collaborator Contribution Able to recruit patients from the hospitalAble to recruit patients from the hospitalSent samples from patients they had recruited at the hospital. Discussions with clinical expert in the sarcoidosis field.Able to recruit patients from the hospital. Discussion with clinical expert in sarcoidosis.
Impact Recruitment of patients
Start Year 2009