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Jenny Cameron
Find out how you can work with the University’s world-class inflammation expertise and state of the art facilities that will provide the solution to your research questions. 
Jenny.Cameron@ei.ed.ac.uk

SteatoSITE is a unique gene-to-outcome data resource which is catalysing multi-sector collaborations to improve the understanding, prevention, and treatment of Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD).

SteatoSITE contains data from 940 patients in Scotland with MASLD - the most common cause of liver disease that affects more than a third of people worldwide.

One in twenty people with MASLD will go on to develop cirrhosis (severe liver scarring), which can lead to fatal health problems including liver complications or associated conditions such as heart disease and non-liver cancers. Being able to predict who is likely to develop these severe outcomes, as well as who is likely to respond to new treatments, could improve outcomes for millions worldwide suffering from MASLD.

SteatoSITE combines tissue-derived metrics and clinical data such as pathology scores, hepatic RNA sequencing, and routine health data from electronic patient records. It was co-created with funding from Innovate UK by the University of Edinburgh and the Precision Medicine Scotland Innovation Centre in Glasgow, using tissue from the NHS Biorepository network and data from 12 of the 14 Scottish National Health Service (NHS) boards through the Scottish Safe Haven Network. The SteatoSITE data commons has now migrated from the University of Glasgow to the University of Edinburgh and is provided via a secure cloud-based data storage platform.

The combined dataset enables research with AI technologies using these multimodal inputs, exemplified by the Innovate UK Eureka-funded international INTErPRET-NAFLD collaboration between University of Edinburgh clinical academic pathology and hepatology investigators and key players at the forefront of NHS AI adoption (Bering, UK), digital pathology (HistoIndex, Singapore) and data preparation (BioDev, UK) to develop impactful tools that meet the needs of global public health.

23 DISC02 Bench2 Bedside Jonathan Fallowfield Body Image
Professor Jonathan Fallowfield

Professor Jonathan Fallowfield of the Institute for Regeneration and Repair, who co-created SteatoSITE with Professor Tim Kendall, said:

The INTErPRET-NAFLD collaboration demonstrates that multimodal human databases like SteatoSITE are the preeminent model for studying complex diseases. It showcases Scotland as an ideal place to undertake healthcare research using real-world data and I hope the approach provides a template for other researchers studying different conditions."
Timothy Kendall 2
Professor Tim Kendall

Co-creator Professor Tim Kendall, said:

The added value of studying the longitudinal real-world clinical data in SteatoSITE over highly curated trial cohorts is that the insights derived are much more readily translatable to clinical practice and the diversity and nuance of real lives."

SteatoSITE is being supported by Edinburgh Innovations (EI), the University of Edinburgh’s commercialisation service. Dr Susan Bodie, Director of Innovation Development and Licensing at EI, said:

This collaboration is a fantastic example of how we can drive innovation in healthcare research using the ‘triple helix’ of partners: the NHS, UK academia, and industry, benefitting from the unique healthcare ecosystem available at Edinburgh BioQuarter."

University of Edinburgh investigators have already received funding from many sources, including GSK, Guts UK, Innovate UK, Enterprise Singapore, Medical Research Council, Wellcome Trust and Horizon Europe to undertake projects that exploit the full potential of the SteatoSITE resource.

Read more

EI's profile on Jonathan Fallowfield

Institute for Regeneration and Repair

SteatoSITE

Related publications

Baptista, C., Esteves, F., Fallowfield, J.A. et al. Deciphering cytochrome P450 reductase role in MASLD: molecular mechanisms and pathophysiological implications. Nat Rev Gastroenterol Hepatol (2026). https://doi.org/10.1038/s41575-026-01202-y

Carlessi R, Kendall TJ, Olynyk JK, et al. Disease-associated hepatocytes are predictive of outcomes and survival in MASLD beyond fibrosis staging. Gut 2026;75:668-670. https://doi.org/10.1136/gutjnl-2025-336627

Van Dijck, E., Van Laere, S., Logie, E. et al. Gradual DNA methylation changes reveal transcription factors implicated in metabolic dysfunction-associated steatotic liver disease progression and epigenetic age acceleration. Clin Epigenet 17, 138 (2025). https://doi.org/10.1186/s13148-025-01945-6

Field DT, Ren Y, Akbary K, Chng E, Tai D, Naoumov NV, Kleiner DE, Fallowfield JA, Kendall TJ, Sanyal AJ. Effect of liver biopsy size on MASLD fibrosis assessment by second-harmonic generation/two-photon excitation fluorescence microscopy. JHEP Rep. 2025 May 8;7(8): 101449. https://doi.org/10.1016/j.jhepr.2025.101449. PMID: 40671833; PMCID: PMC12260414.

Sugimoto, A., Saito, Y., Wang, G. et al. Hepatic stellate cells control liver zonation, size and functions via R-spondin 3. Nature 640, 752–761 (2025). https://doi.org/10.1038/s41586-025-08677-w

Kasarinaite, A., Ramos, M.J., Beltran-Sierra, M. et al. Hormone correction of dysfunctional metabolic gene expression in stem cell-derived liver tissue. Stem Cell Res Ther 16, 130 (2025). https://doi.org/10.1186/s13287-025-04238-0

Perry, A. S., Hadad, N., Chatterjee, E., Jimenez Ramos, M., Farber-Eger, E., Roshani, R., Stolze, L. K., Betti, M. J., Zhao, S., Huang, S., Martens, L., Kendall, T. J., Thone, T., Amancherla, K., Bailin, S., Gabriel, C. L., Koethe, J., Carr, J. J., Terry, J. G., ... Shah, R. (2024). A prognostic molecular signature of hepatic steatosis is spatially heterogeneous and dynamic in human liver. Cell Reports Medicine. https://doi.org/10.1016/j.xcrm.2024.101871

Ramachandran, P., Brice, M., Sutherland, E., Hoy, A., Papachristoforou, E., Li, J., Turner, F., Kendall, T. J., MARWICK, JOHN., Carragher, N. O., Oro, D., Feigh, M., Leeming, D. J., Nielsen, M. J., Karsdal, M. A., Hartmann, N., Erickson, M., Adorini, L., Roth, J. D., & Fallowfield, J. A. (2024). Aberrant basement membrane production by hepatic stellate cells in MASLD is attenuated by the bile acid analog INT-767. Hepatology Communications, 8(12), Article e0574. https://doi.org/10.1097/HC9.0000000000000574

Kendall, T. J., Chng, E., Ren, Y., Tai, D., Ho, G., & Fallowfield, J. A. (2024). Outcome prediction in metabolic dysfunction-associated steatotic liver disease using stain-free digital pathological assessment. Liver International, 44(10), 2511-2516. https://doi.org/10.1111/liv.16062

Drozdov I, Szubert B, Rowe IA, Kendall TJ, Fallowfield JA. Accurate prediction of all-cause mortality in patients with metabolic dysfunction-associated steatotic liver disease using electronic health records. Ann Hepatol. 2024 Sep-Oct;29(5):101528. https://doi.org/10.1016/j.aohep.2024.101528. Epub 2024 Jul 4. PMID: 38971372

Kendall, T.J., Jimenez-Ramos, M., Turner, F. et al. An integrated gene-to-outcome multimodal database for metabolic dysfunction-associated steatotic liver disease. Nat Med 29, 2939–2953 (2023). https://doi.org/10.1038/s41591-023-02602-2

Carlessi R, Denisenko E, Boslem E, Köhn-Gaone J, Main N, Abu Bakar NDB, Shirolkar GD, Jones M, Beasley AB, Poppe D, Dwyer BJ, Jackaman C, Tjiam MC, Lister R, Karin M, Fallowfield JA, Kendall TJ, Forbes SJ, Gray ES, Olynyk JK, Yeoh G, Forrest ARR, Ramm GA, Febbraio MA, Tirnitz-Parker JEE. Single-nucleus RNA sequencing of
pre-malignant liver reveals disease-associated hepatocyte state with HCC prognostic potential. Cell Genom. 2023 Apr 13;3(5):100301. https://doi.org/10.1016/j.xgen.2023.100301. PMID: 37228755; PMCID: PMC10203275.