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Prof Jeremy Tomlinson leads a study to identify non-invasive biomarkers for diagnosing and staging non-alcoholic fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD), a disease of increasing prevalence, is caused by the deposit of excess fat in the liver. Over time, this can lead to inflammation and fibrosis, and, in some cases, the development of serious liver and cardiovascular complications. One such liver complication is hepatocellular cancer (HCC) and people with later stage NAFLD have a nearly 7-fold increased risk of HCC compared to those without liver disease. Better identification and staging of NAFLD would, amongst other things, be beneficial for identifying those at higher risk of HCC development, with the aim of earlier HCC detection.

Since early stage NAFLD is often asymptomatic, it is challenging to diagnose and assess the severity of NAFLD progression early when more effective management strategies can be put in place. Standard diagnostic techniques have their disadvantages: liver biopsy is an invasive and risky procedure, and liver biochemistry, measured by a blood test, is not altered in many cases. A new, less invasive diagnostic approach is therefore needed for better assessment of NAFLD.

Steroid hormones are mainly metabolised in the liver and the products are excreted in the urine. Since steroid hormone metabolic pathways are altered in patients with NAFLD, if these metabolic changes are detectable in the urine, non-invasive assessment of urinary steroids could be used as the basis for a diagnostic and staging test for NAFLD. In a paper published in the journal Alimentary Pharmacology & Therapeutics, Professor Jeremy Tomlinson (Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine) and colleagues from Oxford University Hospitals NHS Foundation Trust and the Universities of Groningen, Birmingham, Nottingham and Antwerp analysed the steroid metabolome in urine using gas chromatography mass spectrometry. They employed unbiased Generalised Matrix Vector Learning Quantisation and were able to separate control patients from patients with NAFLD. Within the NAFLD-affected group, the researchers could also differentiate those at different NAFLD stages and distinguish them from patients with alcohol-related cirrhosis.

With these promising findings, the researchers will now validate the results in a larger, independent prospective cohort. It is hoped that this approach can be extended to detect HCC in NAFLD patients and patients with other chronic liver conditions, and Professor Tomlinson is part of the CRUK-funded DeLIVER consortium, led by Professor Ellie Barnes.

To find out more about HCC early detection research in Oxford, see the liver cancer research showcase.

 

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