Imperial College London


Faculty of MedicineDepartment of Metabolism, Digestion and Reproduction

Professor of Hepatology. Head of Department



+44 (0)20 3312 1903m.thursz




Ms Dawn Campbell +44 (0)20 3312 6454




Norfolk PlaceSt Mary's Campus





Mark Thursz is professor of hepatology at Imperial College and consultant in hepatology at St Mary's Hospital, London. His clinical interests are in viral hepatitis, alcoholic liver disease and fatty liver disease. He is currently interested in developing programmes for treatment of chronic hepatitis B infection in resource poor settings to reduce the risk of hepatocellular carcinoma.

Professor Thursz' research interests are focussed on the natural history of viral hepatitis and fatty liver disease and the factors which determine chronic infection and progressive liver disease. He has a special interest in the genetic determinants of disease outcomes using genetic association and genome wide scanning to identify causative variants.

Professor Thursz is chief investigator on two multi-centre trials: The warfarin anticoagulation for liver fibrosis in patients transplanted for hepatitis C (WAFT-C) trial and the steroids or pentoxifylline for alcoholic hepatitis (STOPAH) trial.

Professor Thursz is a former secretary of the British Association for Study of the Liver (BASL) and is currently vice-secretary of the European Association for Study of the Liver. In this role he has special responsibility for EU policy and advocacy in Brussels.




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Pinato DJ, Guerra N, Fessas P, et al., 2020, Immune-based therapies for hepatocellular carcinoma, Oncogene, ISSN:0950-9232

Forlano R, Mullish BH, Nathwani R, et al., 2019, Non-alcoholic fatty liver disease and vascular disease, Current Vascular Pharmacology, ISSN:1570-1611

Atkinson SR, Hamesch K, Spivak I, et al., 2020, Serum transferrin is an independent predictor of mortality in severe alcoholic hepatitis., American Journal of Gastroenterology, Vol:115, ISSN:0002-9270, Pages:398-405

Forlano R, Mullish BH, Giannakeas N, et al., 2019, High-throughput, machine learning-based quantification of steatosis, inflammation, ballooning, and fibrosis in biopsies from patients with nonalcoholic fatty liver disease, Clinical Gastroenterology and Hepatology, ISSN:1542-3565

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