A prognostic molecular signature of hepatic steatosis is spatially heterogeneous and dynamic in human liver

Hepatic steatosis is a central phenotype in multi-system metabolic dysfunction and is increasing in parallel with the obesity pandemic. We use a translational approach integrating clinical phenotyping and outcomes, circulating proteomics, and tissue transcriptomics to identify dynamic, functional biomarkers of hepatic steatosis. Using multi-modality imaging and broad proteomic profiling, we identify proteins implicated in the progression of hepatic steatosis that are largely encoded by genes enriched at the transcriptional level in the human liver. These transcripts are differentially expressed across areas of steatosis in spatial transcriptomics, and several are dynamic during stages of steatosis. Circulating multi-protein signatures of steatosis strongly associate with fatty liver disease and multi-system metabolic outcomes. Using a humanized "liver-on-a-chip" model, we induce hepatic steatosis, confirming cell-specific expression of prioritized targets. These results underscore the utility of this approach to identify a prognostic, functional, dynamic "liquid biopsy" of human liver, relevant to biomarker discovery and mechanistic research applications.

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Publication Details

Journal
Cell Reports Medicine
Published
2024-12-01
DOI
https://doi.org/10.1016/j.xcrm.2024.101871
Citations
10
Primary Topic
Liver Disease Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
3.87

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article

A prognostic molecular signature of hepatic steatosis is spatially heterogeneous and dynamic in human liver

Andrew Perry, Martin Guilliams, J. Jeffrey Carr, Lindsey K. Stolze et al.
10 citations
Cell Reports Medicine
Liver Disease Diagnosis and Treatment
3.87
article

A prognostic molecular signature of hepatic steatosis is spatially heterogeneous and dynamic in human liver

Andrew Perry, Martin Guilliams, J. Jeffrey Carr, Lindsey K. Stolze, Emeli Chatterjee, Kaushik V Amancherla, Ravi V. Shah, Saumya Das, Niran Hadad, Michael J. Betti, Samuel Bailin, Shi Huang, Susan P. Fisher‐Hoch, E. Dale Abel, Laura A. Colangelo, Eric Farber‐Eger, Jennifer Elizabeth Below, Curtis L. Gabriel, Kendall R. Van Keuren‐Jensen, Matthew Nayor, Eric B. Alsop, Ravi Kalhan, Joseph B. McCormick, James Greg Terry, Quinn S. Wells, Jane E. Freedman, Gautam Mahajan, Kari E. North, John Sauld, Liesbet Martens, Charlotte L. Scott, Timothy James Kendall, Nataraja Sarma Vaitinadin, Shilin Zhao, Maria Jiménez Ramos, Jonathan Andrew Fallowfield, Tinne Thoné, Sadiya S. Khan, Nicholas E. Banovich, John R. Koethe, Kahraman Tanrıverdi, Eric R. Gamazon, Rashedeh Roshani
article en
10 citations

Abstract

Hepatic steatosis is a central phenotype in multi-system metabolic dysfunction and is increasing in parallel with the obesity pandemic. We use a translational approach integrating clinical phenotyping and outcomes, circulating proteomics, and tissue transcriptomics to identify dynamic, functional biomarkers of hepatic steatosis. Using multi-modality imaging and broad proteomic profiling, we identify proteins implicated in the progression of hepatic steatosis that are largely encoded by genes enriched at the transcriptional level in the human liver. These transcripts are differentially expressed across areas of steatosis in spatial transcriptomics, and several are dynamic during stages of steatosis. Circulating multi-protein signatures of steatosis strongly associate with fatty liver disease and multi-system metabolic outcomes. Using a humanized "liver-on-a-chip" model, we induce hepatic steatosis, confirming cell-specific expression of prioritized targets. These results underscore the utility of this approach to identify a prognostic, functional, dynamic "liquid biopsy" of human liver, relevant to biomarker discovery and mechanistic research applications.

Cell Reports MedicineVol. 5(12)
Boston University (US), Northwestern University (US), University of North Carolina at Chapel Hill (US), Translational Genomics Research Institute (US), University of California, Los Angeles (US), Vanderbilt University (US), UCLA Health (US), Massachusetts General Hospital (US), Emulate (United States) (US), MRC Centre for Regenerative Medicine (GB), VIB-UGent Center for Inflammation Research (BE), Vanderbilt University Medical Center (US), The University of Texas Health Science Center at Houston (US), University of Edinburgh (GB)
U.S. Department of Health and Human Services, Northwestern University, University of Minnesota, National Institutes of Health, Kaiser Foundation Research Institute, Center for Clinical and Translational Sciences, University of Texas Health Science Center at Houston, Medical Research Council, National Heart, Lung, and Blood Institute, National Center for Advancing Translational Sciences
Good health and well-being
Openalex Percentile: Top 6%
Liver Disease Diagnosis and Treatment
3.87
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