Identifying functional metabolic shifts in heart failure with the integration of omics data and a heart-specific, genome-scale model

Bonnie V Dougherty; Kristopher D Rawls; Glynis L Kolling; Kalyan C Vinnakota; Anders Wallqvist; Jason A Papin

doi:10.1016/j.celrep.2021.108836

Identifying functional metabolic shifts in heart failure with the integration of omics data and a heart-specific, genome-scale model

Cell Rep. 2021 Mar 9;34(10):108836. doi: 10.1016/j.celrep.2021.108836.

Authors

Bonnie V Dougherty¹, Kristopher D Rawls¹, Glynis L Kolling², Kalyan C Vinnakota³, Anders Wallqvist⁴, Jason A Papin⁵

Affiliations

¹ Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA.
² Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA; Department of Medicine, Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, VA 22908, USA.
³ Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, MD 21702, USA; The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD 20817, USA.
⁴ Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, MD 21702, USA.
⁵ Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA; Department of Medicine, Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, VA 22908, USA; Department of Biochemistry & Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA. Electronic address: papin@virginia.edu.

PMID: 33691118
DOI: 10.1016/j.celrep.2021.108836

Abstract

In diseased states, the heart can shift to use different carbon substrates, measured through changes in uptake of metabolites by imaging methods or blood metabolomics. However, it is not known whether these measured changes are a result of transcriptional changes or external factors. Here, we explore transcriptional changes in late-stage heart failure using publicly available data integrated with a model of heart metabolism. First, we present a heart-specific genome-scale metabolic network reconstruction (GENRE), iCardio. Next, we demonstrate the utility of iCardio in interpreting heart failure gene expression data by identifying tasks inferred from differential expression (TIDEs), which represent metabolic functions associated with changes in gene expression. We identify decreased gene expression for nitric oxide (NO) and N-acetylneuraminic acid (Neu5Ac) synthesis as common metabolic markers of heart failure. The methods presented here for constructing a tissue-specific model and identifying TIDEs can be extended to multiple tissues and diseases of interest.

Keywords: GENRE; N-acetylneuraminic acid; heart failure; heart metabolism; metabolic network; nitric oxide; transcriptomics.

Publication types

Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Databases, Protein
Heart Failure / genetics*
Heart Failure / pathology
Humans
Metabolic Networks and Pathways / genetics*
Metabolomics / methods
Models, Biological*
Myocardium / metabolism*
N-Acetylneuraminic Acid / metabolism
Nitric Oxide / metabolism
Severity of Illness Index

Substances

Nitric Oxide
N-Acetylneuraminic Acid