An integrated gene-to-outcome multimodal database for metabolic dysfunction-associated steatotic liver disease
Timothy J. Kendall, Maria Jiménez Ramos, Frances Turner, Prakash Ramachandran, Jessica Minnier, Michael McColgan, Masood Alam, Harriet Ellis, Donald R. Dunbar, Gabriele Kohnen, Prakash Konanahalli, Karin A. Oien, Lucia Bandiera, Filippo Menolascina, Anna Juncker‐Jensen, Douglas Alexander, Charlie Mayor, Indra Neil Guha, Jonathan Fallowfield
Abstract
Metabolic dysfunction-associated steatotic liver disease (MASLD) is the commonest cause of chronic liver disease worldwide and represents an unmet precision medicine challenge. We established a retrospective national cohort of 940 histologically defined patients (55.4% men, 44.6% women; median body mass index 31.3; 32% with type 2 diabetes) covering the complete MASLD severity spectrum, and created a secure, searchable, open resource (SteatoSITE). In 668 cases and 39 controls, we generated hepatic bulk RNA sequencing data and performed differential gene expression and pathway analysis, including exploration of gender-specific differences. A web-based gene browser was also developed. We integrated histopathological assessments, transcriptomic data and 5.67 million days of time-stamped longitudinal electronic health record data to define disease-stage-specific gene expression signatures, pathogenic hepatic cell subpopulations and master regulator networks associated with adverse outcomes in MASLD. We constructed a 15-gene transcriptional risk score to predict future hepatic decompensation events (area under the receiver operating characteristic curve 0.86, 0.81 and 0.83 for 1-, 3- and 5-year risk, respectively). Additionally, thyroid hormone receptor beta regulon activity was identified as a critical suppressor of disease progression. SteatoSITE supports rational biomarker and drug development and facilitates precision medicine approaches for patients with MASLD.