An integrative systems genetic analysis of mammalian lipid metabolism
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 proteo...
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| Published in | Nature (London) Vol. 567; no. 7747; pp. 187 - 193 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
01.03.2019
Nature Publishing Group |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0028-0836 1476-4687 1476-4687 |
| DOI | 10.1038/s41586-019-0984-y |
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| 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. |
|---|---|
| AbstractList | 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 lipidrelated 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. 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. 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.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. 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. 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. 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. |
| Audience | Academic |
| Author | Miller, Matthew L. Weir, Jacquelyn M. Clifford, Bethan L. Drew, Brian G. Lazarus, Ross Pan, Calvin Jayawardana, Kaushala de Aguiar Vallim, Thomas Q. Needham, Elise J. Tarling, Elizabeth J. Liu, Yingying Meex, Ruth C. R. Lee, Richard Peng, Kang-Yu Mellett, Natalie A. Moody, Sarah C. Watt, Matthew J. Yang, Pengyi James, David E. Meikle, Peter J. Calkin, Anna C. Keating, Michael F. Morand, Pauline Lusis, Aldons J. Zerenturk, Eser J. Parker, Benjamin L. Seldin, Marcus M. |
| AuthorAffiliation | 13 These authors contributed equally: Benjamin L. Parker, Anna C. Calkin, Marcus M. Seldin 1 Metabolic Systems Biology Laboratory, Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales, Australia 4 Department of Human Genetics/Medicine, David Geffen School of Medicine, University of California Los Angeles (UCLA), Los Angeles, CA, USA 2 Lipid Metabolism & Cardiometabolic Disease Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia 7 Molecular Biology Institute, University of California Los Angeles (UCLA), Los Angeles, CA, USA 10 Department of Physiology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia 9 Department of Biological Chemistry, David Geffen School of Medicine, University of California Los Angeles (UCLA), Los Angeles, CA, USA 6 Department of Medicine, Division of Cardiology, University of California Los Angeles (UCLA), Los Angeles, CA, USA 11 M |
| AuthorAffiliation_xml | – name: 1 Metabolic Systems Biology Laboratory, Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales, Australia – name: 14 These authors jointly supervised this work: Thomas Q. de Aguiar Vallim, Brian G. Drew – name: 9 Department of Biological Chemistry, David Geffen School of Medicine, University of California Los Angeles (UCLA), Los Angeles, CA, USA – name: 11 Metabolomics Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia – name: 5 Molecular Metabolism & Ageing Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia – name: 7 Molecular Biology Institute, University of California Los Angeles (UCLA), Los Angeles, CA, USA – name: 4 Department of Human Genetics/Medicine, David Geffen School of Medicine, University of California Los Angeles (UCLA), Los Angeles, CA, USA – name: 3 Central Clinical School, Department of Medicine, Monash University, Melbourne, Victoria, Australia – name: 2 Lipid Metabolism & Cardiometabolic Disease Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia – name: 6 Department of Medicine, Division of Cardiology, University of California Los Angeles (UCLA), Los Angeles, CA, USA – name: 13 These authors contributed equally: Benjamin L. Parker, Anna C. Calkin, Marcus M. Seldin – name: 8 Charles Perkins Centre, School of Mathematics and Statistics, University of Sydney, Sydney, New South Wales, Australia – name: 12 Ionis Therapeutics Inc., Carlsbad, CA, USA – name: 10 Department of Physiology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia |
| Author_xml | – sequence: 1 givenname: Benjamin L. surname: Parker fullname: Parker, Benjamin L. organization: Metabolic Systems Biology Laboratory, Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney – sequence: 2 givenname: Anna C. surname: Calkin fullname: Calkin, Anna C. email: anna.calkin@baker.edu.au organization: Lipid Metabolism & Cardiometabolic Disease Laboratory, Baker Heart & Diabetes Institute, Central Clinical School, Department of Medicine, Monash University – sequence: 3 givenname: Marcus M. surname: Seldin fullname: Seldin, Marcus M. organization: Department of Human Genetics/Medicine, David Geffen School of Medicine, University of California Los Angeles (UCLA) – sequence: 4 givenname: Michael F. surname: Keating fullname: Keating, Michael F. organization: Lipid Metabolism & Cardiometabolic Disease Laboratory, Baker Heart & Diabetes Institute, Central Clinical School, Department of Medicine, Monash University, Molecular Metabolism & Ageing Laboratory, Baker Heart & Diabetes Institute – sequence: 5 givenname: Elizabeth J. surname: Tarling fullname: Tarling, Elizabeth J. organization: Department of Medicine, Division of Cardiology, University of California Los Angeles (UCLA), Molecular Biology Institute, University of California Los Angeles (UCLA) – sequence: 6 givenname: Pengyi surname: Yang fullname: Yang, Pengyi organization: Charles Perkins Centre, School of Mathematics and Statistics, University of Sydney – sequence: 7 givenname: Sarah C. surname: Moody fullname: Moody, Sarah C. organization: Lipid Metabolism & Cardiometabolic Disease Laboratory, Baker Heart & Diabetes Institute, Molecular Metabolism & Ageing Laboratory, Baker Heart & Diabetes Institute – sequence: 8 givenname: Yingying surname: Liu fullname: Liu, Yingying organization: Lipid Metabolism & Cardiometabolic Disease Laboratory, Baker Heart & Diabetes Institute, Molecular Metabolism & Ageing Laboratory, Baker Heart & Diabetes Institute – sequence: 9 givenname: Eser J. surname: Zerenturk fullname: Zerenturk, Eser J. organization: Lipid Metabolism & Cardiometabolic Disease Laboratory, Baker Heart & Diabetes Institute, Molecular Metabolism & Ageing Laboratory, Baker Heart & Diabetes Institute – sequence: 10 givenname: Elise J. surname: Needham fullname: Needham, Elise J. organization: Metabolic Systems Biology Laboratory, Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney – sequence: 11 givenname: Matthew L. surname: Miller fullname: Miller, Matthew L. organization: Molecular Biology Institute, University of California Los Angeles (UCLA) – sequence: 12 givenname: Bethan L. surname: Clifford fullname: Clifford, Bethan L. organization: Department of Medicine, Division of Cardiology, University of California Los Angeles (UCLA) – sequence: 13 givenname: Pauline surname: Morand fullname: Morand, Pauline organization: Department of Biological Chemistry, David Geffen School of Medicine, University of California Los Angeles (UCLA) – sequence: 14 givenname: Matthew J. surname: Watt fullname: Watt, Matthew J. organization: Department of Physiology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne – sequence: 15 givenname: Ruth C. R. surname: Meex fullname: Meex, Ruth C. R. organization: Department of Physiology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne – sequence: 16 givenname: Kang-Yu surname: Peng fullname: Peng, Kang-Yu organization: Metabolomics Laboratory, Baker Heart & Diabetes Institute – sequence: 17 givenname: Richard surname: Lee fullname: Lee, Richard organization: Ionis Therapeutics Inc – sequence: 18 givenname: Kaushala surname: Jayawardana fullname: Jayawardana, Kaushala organization: Metabolomics Laboratory, Baker Heart & Diabetes Institute – sequence: 19 givenname: Calvin surname: Pan fullname: Pan, Calvin organization: Department of Human Genetics/Medicine, David Geffen School of Medicine, University of California Los Angeles (UCLA) – sequence: 20 givenname: Natalie A. surname: Mellett fullname: Mellett, Natalie A. organization: Metabolomics Laboratory, Baker Heart & Diabetes Institute – sequence: 21 givenname: Jacquelyn M. surname: Weir fullname: Weir, Jacquelyn M. organization: Metabolomics Laboratory, Baker Heart & Diabetes Institute – sequence: 22 givenname: Ross surname: Lazarus fullname: Lazarus, Ross organization: Metabolomics Laboratory, Baker Heart & Diabetes Institute – sequence: 23 givenname: Aldons J. surname: Lusis fullname: Lusis, Aldons J. organization: Department of Human Genetics/Medicine, David Geffen School of Medicine, University of California Los Angeles (UCLA) – sequence: 24 givenname: Peter J. surname: Meikle fullname: Meikle, Peter J. organization: Metabolomics Laboratory, Baker Heart & Diabetes Institute – sequence: 25 givenname: David E. surname: James fullname: James, David E. organization: Metabolic Systems Biology Laboratory, Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney – sequence: 26 givenname: Thomas Q. surname: de Aguiar Vallim fullname: de Aguiar Vallim, Thomas Q. email: tvallim@mednet.ucla.edu organization: Department of Medicine, Division of Cardiology, University of California Los Angeles (UCLA), Molecular Biology Institute, University of California Los Angeles (UCLA), Department of Biological Chemistry, David Geffen School of Medicine, University of California Los Angeles (UCLA) – sequence: 27 givenname: Brian G. surname: Drew fullname: Drew, Brian G. email: brian.drew@baker.edu.au organization: Central Clinical School, Department of Medicine, Monash University, Molecular Metabolism & Ageing Laboratory, Baker Heart & Diabetes Institute |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30814737$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | The Author(s), under exclusive licence to Springer Nature Limited 2019 COPYRIGHT 2019 Nature Publishing Group Copyright Nature Publishing Group Mar 14, 2019 |
| Copyright_xml | – notice: The Author(s), under exclusive licence to Springer Nature Limited 2019 – notice: COPYRIGHT 2019 Nature Publishing Group – notice: Copyright Nature Publishing Group Mar 14, 2019 |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Author contributions B.G.D., T.Q.d.A.V., A.C.C. and E.J.T. conceived the original concept. B.G.D., T.Q.d.A.V, A.C.C., B.L.P., M.M.S. and D.E.J. conceptualized the study and designed, performed, oversaw, interpreted and generated data and figures. B.L.P. and D.E.J. generated, analysed and interpreted the proteomic datasets. P.J.M. supervised the generation, analysis and interpretation of lipidomics data. A.J.L. advised on study design and systems genetics analysis, and provided access to data, software and reagents. B.G.D., B.L.P., T.Q.d.A.V., M.M.S., A.C.C., M.F.K., S.C.M., Y.L., E.J.Z., N.A.M., E.J.N., M.L.M., B.L.C., P.M., M.J.W., R.C.R.M., K.-Y.P., R. Lazarus and J.M.W. provided reagents, generated data and contributed to figure production. Specifically, B.L.C., P.M. and M.L.M. performed and analysed in vivo ASO experiments and data, and M.J.W., R.C.R.M. and K.-Y.P. performed and provided data for human plasma lipid signature validations. R. Lee provided access to, and expertise pertaining to ASO generation and delivery. M.M.S., B.L.P., B.G.D., K.J., C.P., R. Lazarus and P.Y. performed bioinformatics analyses. B.G.D., B.L.P., T.Q.d.A.V., A.C.C., M.M.S. and D.E.J. wrote the manuscript. All authors read and edited the manuscript. |
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| Title | An integrative systems genetic analysis of mammalian lipid metabolism |
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