Author information
1Vanderbilt University School of Medicine, Nashville, TN, USA.
2Translational Genomics Research Institute, Phoenix, AZ, USA.
3Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
4Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, UK.
5Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
6Laboratory of Myeloid Cell Biology in Tissue Homeostasis and Regeneration, VIB-UGent Center for Inflammation Research, Ghent, Belgium; Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium.
7Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, UK; Edinburgh Pathology, University of Edinburgh, Edinburgh, UK.
8Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
9Emulate Inc., Boston, MA, USA.
10Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
11Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
12Sections of Cardiovascular Medicine and Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA.
13School of Public Health, The University of Texas Health Science Center at Houston, Brownsville, TX, USA.
14CVD Genetic Epidemiology Computational Laboratory, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
15Department of Medicine, David Geffen School of Medicine and UCLA Health, University of California-Los Angeles, Los Angeles, CA, USA.
16Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, UK. Electronic address: jonathan.fallowfield@ed.ac.uk.
17Translational Genomics Research Institute, Phoenix, AZ, USA. Electronic address: nbanovich@tgen.org.
18Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA. Electronic address: sdas@mgh.harvard.edu.
19Vanderbilt University School of Medicine, Nashville, TN, USA. Electronic address: ravi.shah@vumc.org.
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.