Identifying the biological fingerprints of fatigue

Context of the research:
Chronic fatigue syndrome (CFS) affects 1 in 300 people in the UK and is associated with a significant healthcare-related cost to the society. Severe, persistent fatigue is a key symptom of CFS and a major factor leading to loss of productivity in this illness. The cause of CFS and the underlying biological mechanisms of fatigue are poorly understood. As a result, accurate diagnosis of CFS can be difficult and effective treatment is not available. A growing body of evidence suggests that CFS may be linked to a faulty immune system. However, in what ways the immune system is not working properly is not clear. Therefore, by uncovering the abnormalities of the immune system in CFS in detail, it will help make the diagnosis of CFS easier and more accurate as well as give us clues to develop effective treatment of this condition.

Since the diagnosis of CFS is unreliable at present, a group of "CFS" patients may in fact consist of individuals with different diseases. This presents a major obstacle to the progress of CFS research and may also explain why data from different CFS research studies are often conflicting. Therefore, in order to better understand the underlying biological mechanisms of CFS, a different approach is needed. Recent data show that intense fatigue is also a common symptom for many chronic conditions. Interestingly, most of these conditions are due to a faulty immune system. Furthermore, research also suggests that severe fatigue in these various conditions is driven by similar biological mechanisms. If so, we may be able to find out the underlying defects of the immune system causing disabling fatigue in CFS by using one of these chronic conditions as a disease model. This is precisely what we will do in this study.

We will carry out a comprehensive analysis of the immune system of a large number of patients with a condition called primary Sjögren syndrome (PSS). We will analyze the data obtained from these experiments to find out what abnormalities of the immune system are linked to fatigue. Since these experiments typically produce a vast amount of data, we will apply statistical methods and mathematical modelling specifically designed to analyse large volumes of biological data (known as bioinformatics and biostatistics) in order to identify the biological "fingerprints" of fatigue. We will then test whether these biological fingerprints of fatigue are present in CFS patients and whether it will help us to diagnose CFS more accurately.

We chose PSS as a disease model for several reasons. (i) PSS and CFS have many shared clinical and biological features including profound fatigue. (ii) Clinical samples from over 550 PSS patients across the UK, as well as their clinical data, are available for this study. Access to such samples is a distinct advantage because this is one of the largest clinical sample collections in PSS in the world. It would be time-consuming, labour-intensive and expensive if we had needed to collect the same amount of clinical samples and accompanied clinical data from fresh. (iii) There are well-established diagnostic criteria for PSS and so this avoids the problem of studying patients with potentially mixed diagnoses as in the case of studying CFS patients.

Aims of the study, potential applications and benefits:
The main objective of this study is to find the biological fingerprints of fatigue. By doing so, it will improve our understanding of the biological mechanisms of fatigue. The data will enable us to develop treatments for the fatigue that plagues so many patients with CFS and other chronic conditions. It will also help us to design a clinical test for the diagnosis of CFS.

This study aims to identify the biological fingerprints of fatigue using primary Sjogren's syndrome (PSS), an autoimmune condition with several clinical and biological features similar to chronic fatigue syndrome (CFS) including intense fatigue, as a disease model. We will then test whether these biological fingerprints are also present in patients with CFS.

We will perform whole blood gene expression profiling (using genome-wide microarray) and measure serum markers of immune dysregulation (using fluorescent bead-based multiplex technology) of an existing biobanked samples from a large cohort of clinically well-characterized PSS patients (the UK PSS registry). Further information concerning the cohort can be found on the cohort website www.sjogrensregistry.org and Annex 1. The data from these experiments will be analyzed using various bioinformatics techniques in order to identify a biological profile of fatigue, which will be validated using a second blinded test cohort of PSS patients. We will also investigate whether the biological profile changes over time and responds to biological treatment of fatigue in PSS patients. The data from these investigations will then be integrated to identify a set of biomarkers that will maximally discriminate fatigued subjects from non-fatigued individuals. Finally, we will test whether these biomarkers of fatigue are present in CFS patients and if so, whether they can be used to correctly classify CFS from active or sedentary healthy individuals.

Chronic fatigue is a global health problem. Severe, debilitating fatigue is not only the cardinal symptom of chronic fatigue syndrome (CFS), but also a common problem in many chronic diseases, cancers and a side-effect of many treatments such as cytokine-based therapies and chemotherapies. In the wider health-economic context, chronic fatigue is a common complaint in primary care settings and is a major cause of productivity loss at work places and associated poor quality of life. It places a considerable burden on the NHS. It has been estimated to cost over £633 millions every year in a survey carried out in 2000. In the US, a study in 2009 estimated an annual loss of over US$136 billion in productivity.

Despite being a common symptom, fatigue is a poorly understood phenomenon and the treatment of fatigue is largely ineffective. In addition, adequate assessment of a complex, multi-faceted symptom such as fatigue remains a challenge to researchers and clinicians alike.

Therefore, by seeking the biological fingerprints of fatigue using a hypothesis-free approach, the data generated from this study will have a substantial scientific and societal impact. In the short term, it will address a key knowledge gap in the biological mechanisms of fatigue and CFS as well as inform future directions of research in these areas. The development of a recognized biomarker would ease the stigma sometimes associates with CFS/ME through the lack of such a diagnostic.

In the longer term, the biomarkers of fatigue identified in this proposal can be used to study chronic fatigue in other conditions. These biomarkers may also facilitate the development of targeted therapies, provide an objective assessment of responses to treatments in clinical trials and improve our diagnosis and stratification of fatigue and CFS. The development of any drugs or therapies would be of potential benefit to pharmaceutical companies and the economy.