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An integrated gene-to-outcome multimodal database for metabolic dysfunction-associated steatotic liver disease.

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.

SUBMITTER: Kendall TJ

PROVIDER: S-EPMC10667096 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

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An integrated gene-to-outcome multimodal database for metabolic dysfunction-associated steatotic liver disease.

Kendall Timothy J TJ Jimenez-Ramos Maria M Turner Frances F Ramachandran Prakash P Minnier Jessica J McColgan Michael D MD Alam Masood M Ellis Harriet H Dunbar Donald R DR Kohnen Gabriele G Konanahalli Prakash P Oien Karin A KA Bandiera Lucia L Menolascina Filippo F Juncker-Jensen Anna A Alexander Douglas D Mayor Charlie C Guha Indra Neil IN Fallowfield Jonathan A JA

Nature medicine 20231030 11

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 hepat ...[more]

PMID: 37903863

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Project description:ImportanceIn the US, hepatocellular carcinoma (HCC) has been the most rapidly increasing cancer since 1980, and metabolic dysfunction-associated steatotic liver disease (MASLD) is expected to soon become the leading cause of HCC.ObjectiveTo develop a prediction model for HCC incidence in a cohort of patients with MASLD.Design, setting, and participantsThis prognostic study was conducted among patients aged at least 18 years with MASLD, identified using diagnosis of MASLD using International Classification of Diseases, Ninth Revision (ICD-9) or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) diagnosis codes; natural language processing of radiology imaging report text, which identified patients who had imaging evidence of MASLD but had not been formally diagnosed; or the Dallas Steatosis Index, a risk equation that identifies individuals likely to have MASLD with good precision. Patients were enrolled from Kaiser Permanente Northern California, an integrated health delivery system with more than 4.6 million members, with study entry between January 2009 and December 2018, and follow-up until HCC development, death, or study termination on September 30, 2021. Statistical analysis was performed during February 2023 and January 2024.ExposureData were extracted from the electronic health record and included 18 routinely measured factors associated with MASLD.Main outcome and measuresThe cohort was split (70:30) into derivation and internal validation sets; extreme gradient boosting was used to model HCC incidence. HCC risk was divided into 3 categories, with the cumulative estimated probability of HCC 0.05% or less classified as low risk; 0.05% to 0.09%, medium risk; and 0.1% or greater, high risk.ResultsA total of 1 811 461 patients (median age [IQR] at baseline, 52 [41-63] years; 982 300 [54.2%] female) participated in the study. During a median (range) follow-up of 9.3 (5.8-12.4) years, 946 patients developed HCC, for an incidence rate of 0.065 per 1000 person-years. The model achieved an area under the curve of 0.899 (95% CI, 0.882-0.916) in the validation set. At the medium-risk threshold, the model had a sensitivity of 87.5%, specificity of 81.4%, and a number needed to screen of 406. At the high-risk threshold, the model had a sensitivity of 78.4%, a specificity of 90.1%, and a number needed to screen of 241.Conclusions and relevanceThis prognostic study of more than 1.8 million patients with MASLD used electronic health record data to develop a prediction model to discriminate between individuals with and without incident HCC with good precision. This model could serve as a starting point to identify patients with MASLD who may need intervention and/or HCC surveillance.

Project description:Background and Objectives: As a key mechanism of metabolic dysfunction-associated steatotic liver disease (MASLD) pathogenesis, inflammation triggered by chronic liver injury and immune cells with macrophages enables MASLD to progress to an advanced stage with irreversible processes such as fibrosis, cell necrosis, and cancer in the liver. The complexity of MASLD, including crosstalk between multiple organs and the liver, makes developing a new drug for MASLD challenging, especially in single-drug therapy. It was reported that upregulation of Notch1 is closely associated with the function of pro-inflammatory macrophages. To leverage this signaling pathway in treating MASLD, we developed a combination therapy. Materials and Methods: We chose Notch1 siRNA (siNotch1) to block the Notch pathway so that phenotypic regulation and functional recovery can be achieved in macrophages, combining with small molecule drug AMD3100. AMD3100 can cut off the migration of inflammatory cells to the liver to impede the development of inflammation and inhibit the CXCL12/CXCR4 biological axis in liver fibrosis to protect against the activation of HSCs. Then, we investigated the efficacy of the combination therapy on resolving inflammation and MASLD. Results: We demonstrated that in liver cells, siNotch1 combined with AMD3100 not only directly modulated macrophages by downregulating multiple pathways downstream of Notch, exerting anti-inflammatory, anti-migration, and switch of macrophage phenotype, but also modulated macrophage phenotypes through inhibiting NET release. The restored macrophages further regulate HSC and neutrophils. In in vivo pharmacodynamic studies, combination therapy exhibits a superior therapeutical effect over monotherapy in MASLD models. Conclusions: These results constitute an siRNA therapeutical approach combined with a small molecule drug against inflammation and liver injury in MASLD, offering a promising therapeutic intervention for MASLD.

Dataset Information

An integrated gene-to-outcome multimodal database for metabolic dysfunction-associated steatotic liver disease.

Publications

An integrated gene-to-outcome multimodal database for metabolic dysfunction-associated steatotic liver disease.

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