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An integrative systems genetic analysis of mammalian lipid metabolism

Authors :
Michael F. Keating
Kaushala S. Jayawardana
Elizabeth J. Tarling
Pengyi Yang
Benjamin L. Parker
Pauline Morand
Matthew J. Watt
Thomas Q. de Aguiar Vallim
Marcus M. Seldin
Matthew L. Miller
Richard T. Lee
Eser J. Zerenturk
Yingying Liu
Ruth C. R. Meex
Aldons J. Lusis
Brian G. Drew
Sarah C. Moody
David E. James
Calvin Pan
Natalie A. Mellett
Peter J. Meikle
Jacquelyn M. Weir
Ross Lazarus
Elise J. Needham
Anna C. Calkin
Bethan L. Clifford
Kang-Yu Peng
Source :
Nature, vol 567, iss 7747
Publication Year :
2019
Publisher :
eScholarship, University of California, 2019.

Abstract

Dysregulation of lipid homeostasis is a precipitating event in the pathogenesis and progression of hepatosteatosis and metabolic syndrome. These conditions are highly prevalent in developed societies and currently have limited options for diagnostic and therapeutic intervention. Here, using a proteomic and lipidomic-wide systems genetic approach, we interrogated lipid regulatory networks in 107 genetically distinct mouse strains to reveal key insights into the control and network structure of mammalian lipid metabolism. These include the identification of plasma lipid signatures that predict pathological lipid abundance in the liver of mice and humans, defining subcellular localization and functionality of lipid-related proteins, and revealing functional protein and genetic variants that are predicted to modulate lipid abundance. Trans-omic analyses using these datasets facilitated the identification and validation of PSMD9 as a previously unknown lipid regulatory protein. Collectively, our study serves as a rich resource for probing mammalian lipid metabolism and provides opportunities for the discovery of therapeutic agents and biomarkers in the setting of hepatic lipotoxicity. The integration of liver and plasma quantitative lipidomic and proteomic data from 107 distinct mouse strains provides important insights into regulators of mammalian lipid metabolism.

Details

Database :
OpenAIRE
Journal :
Nature, vol 567, iss 7747
Accession number :
edsair.doi.dedup.....8b1bfa88bea79f16882362b6b6eb9b61