Deep proteome profiling of metabolic dysfunction-associated steatotic liver disease
Abstract Background Metabolic dysfunction-associated steatotic liver disease (MASLD) affects roughly 1 in 3 adults and is a leading cause of liver transplants and liver related mortality. A deeper understanding of disease pathogenesis is essential to assist in developing blood-based biomarkers. Meth...
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| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-03-01
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| Series: | Communications Medicine |
| Online Access: | https://doi.org/10.1038/s43856-025-00780-3 |
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| Summary: | Abstract Background Metabolic dysfunction-associated steatotic liver disease (MASLD) affects roughly 1 in 3 adults and is a leading cause of liver transplants and liver related mortality. A deeper understanding of disease pathogenesis is essential to assist in developing blood-based biomarkers. Methods Here, we use data-independent acquisition mass spectrometry to assess disease-state associated protein profiles in human liver, blood plasma, and white adipose tissue (WAT). Results In liver, we find that MASLD is associated with an increased abundance of proteins involved in immune response and extracellular matrix (ECM) and a decrease in proteins involved in metabolism. Cell type deconvolution of the proteome indicates liver endothelial and hepatic stellate cells are the main source of ECM rearrangements, and hepatocytes are the major contributor to the changes in liver metabolism. In the blood, profiles of several MASLD-associated proteins correlate with expression in WAT rather than liver and so could serve as suitable liver disease predictors in a multi-protein panel marker. Moreover, our proteomics-based logistic regression models perform better than existing methods for predicting MASLD and liver fibrosis from human blood samples. Conclusions Our comprehensive proteomic analysis deepens the understanding of liver function and MASLD pathology by elucidating key cellular mechanisms and multi-organ interactions, and demonstrates the robustness of a proteomics-based biomarker panel to enhance diagnosis of MASLD and significant fibrosis. |
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| ISSN: | 2730-664X |