Abstract P3020: A prognostic molecular signature of hepatic steatosis is spatially heterogeneous and dynamic in human liver
Abstract
Introduction: The prevalence of hepatic steatosis—a central and early phenotype in multi-system metabolic dysfunction—is increasing in parallel with the obesity pandemic, calling for novel approaches for prevention and treatment. Hypothesis: We hypothesized that the circulating proteome may reflect cell specific mechanisms of hepatic steatosis. Methods: Using multi-modality hepatic imaging and broad circulating proteomics in approximately 5,000 individuals across 3 diverse cohorts (CARDIA, Cameron County Hispanic Cohort, UK Biobank), we identified proteins implicated in the progression of hepatic steatosis. We tested for a relationship with these proteomic markers of hepatic steatosis with metabolic-related clinical outcomes in UK Biobank. We translated these findings from the circulating proteome to several tissue-based datasets including bulk RNA sequencing, single-cell RNA sequencing, and spatial transcriptomics. To further prove the hepatocyte origin of prioritized proteins, we used a humanized “liver-on-a-chip” model. Results: We observed proteins implicated in the progression of hepatic steatosis—such as those related to central carbon and amino acid metabolism, hepatocyte regeneration, inflammation, fibrosis, insulin sensitivity—are largely encoded by genes enriched at the transcriptional level in human liver. Circulating multi-protein signatures of hepatic steatosis were strongly associated with a fatty liver disease phenotype and multi-system metabolic outcomes in >26,000 free-living individuals. Moreover, we observed increased activity of transcripts encoding proteins prioritized in clinical studies spatially in areas of steatosis via spatial transcriptomics in human liver, with several top candidates dynamic during progression of steatosis in human liver. Finally, using a humanized “liver-on-a-chip” model, we induced hepatic steatosis, confirming cell-specific expression of targets implicated across tissue and clinical studies at a transcriptional and proteomic level. Conclusions: These results underscore the utility of a unified approach that combines human studies, multi-omics, and dynamic tissue-on-a-chip experiments to identify a prognostic, functional, dynamic “liquid biopsy” of human liver, with relevance for clinical biomarker discovery and mechanistic research applications.
Article Details
Authors (43)
Andrew Perry
Vanderbilt University Medical Center, Nashville, TN (L.K.S., A.P., P.L., Q.S., S.Z., K.A., E.R.G., R.V.S.).
Niran Hadad
Translational Genomics Research Institute, Phoenix, Arizona, United States
Emeli Chatterjee
Massachusetts General Hospital, Boston, Massachusetts, United States
Maria Jimenez Ramos
Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, United Kingdom
Eric Farber-Eger
Rashedeh Roshani
Lindsey Stolze
Vanderbilt University Medical Cente, Nashville, Tennessee, United States
Michael Betti
Vanderbilt University Medical Center, Nashville, Tennessee, United States
Shilin Zhao
Department of Biostatistics, Vanderbilt University Medical Center
Shi Huang
Faculty of Dentistry, University of Hong Kong
Liesbet Martens
Timothy Kendall
Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, United Kingdom
Tinne Thone
Ghent University, Ghent, Belgium
Kaushik Amancherla
Samuel Bailin
Vanderbilt University Medical Cente, Nashville, Tennessee, United States
Curtis Gabriel
Vanderbilt University, Nashville, Tennessee, United States
John Koethe
Vanderbilt University Medical Cente, Nashville, Tennessee, United States
John Carr
Vanderbilt University, Nashville, Tennessee, United States
James Terry
Vanderbilt Univ Medical Center, Nashville, Tennessee, United States
Nataraja Sarma Vaitinadin
Vanderbilt University Medical Center, Nashville, Tennessee, United States
Jane Freedman
Vanderbilt University, Nashville, Tennessee, United States
Kahraman Tanriverdi
Vanderbilt University Medical Cente, Nashville, Tennessee, United States
Eric Alsop
TGen, Phoenix, Arizona, United States
Kendall Van Keuren-Jensen
John Sauld
Emulate Inc, Boston, Massachusetts, United States
Gautam Mahajan
Emulate Inc, Boston, Massachusetts, United States
Sadiya Khan
Northwestern University, Chicago, Illinois, United States
Laura Colangelo
Northwestern University, Chicago, Illinois, United States
Matthew Nayor
Susan Fisher-hoch
UT HOUSTON SCHOOL OF PUBLIC HEALTH, Brownsville, Texas, United States
Joseph B McCormick
The University of Texas Health, Brownsville, Texas, United States
Kari North
UNIV OF TX HEALTH SCI CTR HOUSTON, Houston, Texas, United States
Jennifer Below
Vanderbilt University Medical Center, Nashville, Tennessee, United States
Quinn Wells
VANDERBILT UNIVERSITY, Nashville, Tennessee, United States
Dale Abel
University of California - Los Angeles, Los Angeles, California, United States
Ravi Kalhan
Northwestern University, Oak Park, Illinois, United States
Charlotte Scott
Ghent University, Ghent, Belgium
Martin Guilliams
Eric Gamazon
Jonathan Fallowfield
Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, United Kingdom
Nicholas Banovich
Translational Genomics Research Institute, Phoenix, Arizona, United States
Saumya Das
Ravi Shah