School of Computing


Identifying the Biological Fingerprints of Fatigue

Chronic Fatigue Syndrome (CFS) affects around 250,000 people in the UK. As the name indicates, one of the defining symptoms of the condition is ongoing fatigue, which can range from mild - sufferers can still work, but may require days off to rest - to very severe, forcing patients to stay in bed for most of the day. CFS may last for years. The causes of CFS are still unknown, and there is no diagnostic test for the condition. Ongoing fatigue is also a symptom of several other conditions, one of which is Primary Sjogren's Syndrome (PSS), an autoimmune disease. There is a UK-wide Registry of clinically well-characterized patients with PSS (UKPSSR), which contains data from biobanked peripheral blood mononuclear cells, serum, DNA and RNA.

In this project we aim to identify biomarkers for fatigue in collaboration with Professor Fai Ng. Although debilitating fatigue is very common in PSS, some PSS patients suffer minimal symptom of fatigue. Interestingly, correlation between fatigue and systemic or glandular disease activity of PSS is poor, suggesting that distinct biological processes may be responsible for PSS disease activity and fatigue. Therefore, by comparing and contrasting the biological profiles of PSS patients discordant for the symptom of fatigue, it may be possible to identify a "biological signature"? that is specific for fatigue.

Our contribution to the project is in the areas of statistics and computational biology. We will apply well-characterised statistical approaches, as well as data integration, network analysis and computational intelligence, to the analysis of the PSS data, and the investigation of the applicability of these results to CF patients.