1
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Li X, Morel JD, Sulc J, De Masi A, Lalou A, Benegiamo G, Poisson J, Liu Y, Von Alvensleben GVG, Gao AW, Bou Sleiman M, Auwerx J. Systems genetics of metabolic health in the BXD mouse genetic reference population. Cell Syst 2024; 15:497-509.e3. [PMID: 38866010 DOI: 10.1016/j.cels.2024.05.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 02/29/2024] [Accepted: 05/20/2024] [Indexed: 06/14/2024]
Abstract
Susceptibility to metabolic syndrome (MetS) is dependent on genetics, environment, and gene-by-environment interactions, rendering the study of underlying mechanisms challenging. The majority of experiments in model organisms do not incorporate genetic variation and lack specific evaluation criteria for MetS. Here, we derived a continuous metric, the metabolic health score (MHS), based on standard clinical parameters and defined its molecular signatures in the liver and circulation. In human UK Biobank, the MHS associated with MetS status and was predictive of future disease incidence, even in individuals without MetS. Using quantitative trait locus analyses in mice, we found two MHS-associated genetic loci and replicated them in unrelated mouse populations. Through a prioritization scheme in mice and human genetic data, we identified TNKS and MCPH1 as candidates mediating differences in the MHS. Our findings provide insights into the molecular mechanisms sustaining metabolic health across species and uncover likely regulators. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Xiaoxu Li
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Jean-David Morel
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Jonathan Sulc
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Alessia De Masi
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Amélia Lalou
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Giorgia Benegiamo
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Johanne Poisson
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Yasmine Liu
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Giacomo V G Von Alvensleben
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Arwen W Gao
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Maroun Bou Sleiman
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Johan Auwerx
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.
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2
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Li Y, Guo H, Yang X, Yang X, Zhang H, Wang P, Song J, Wang L, Zhang W, Wen P. Pseudo-targeted lipidomics insights into lipid discrepancies between yak colostrum and mature milk based on UHPLC-Qtrap-MS. Food Chem 2024; 442:138462. [PMID: 38245985 DOI: 10.1016/j.foodchem.2024.138462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 01/11/2024] [Accepted: 01/14/2024] [Indexed: 01/23/2024]
Abstract
Yak milk is essential to maintain the normal physiological functions of herders in Tibetan areas of China. However, the lipid components of yak colostrum (YC) and mature milk (YM) have not been systematically studied. We employed a quantitative lipidomics to comprehensively describe the alterations in the milk lipid profile of lactating yaks. Herein, totally 851 lipids from 28 lipid subclasses in YC and YM were identified and screened for 43 significantly different lipids (SDLs; variable importance in projection > 1, fold change < 0.5 or > 2 with P < 0.05), with cholesterol ester (CE, 16:0) and triacylglycerol (TAG, 54:6 (20:5), 50:1 (16:0), 56:6 (20:5)) were the potential lipid biomarkers. Fourteen SDLs were modulated downwards, and 29 SDLs were modulated upwards in YM. Moreover, by analyzing lipid metabolic pathways in these SDLs, glycerophospholipid metabolism was the most critical. Our results furnish integral lipid details for evaluating yak milk's nutritional quality.
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Affiliation(s)
- Yiheng Li
- College of Food Science and Engineering, Gansu Agricultural University, Lanzhou 730070, China
| | - Huiyuan Guo
- Department of Nutrition and Health, China Agricultural University, Beijing 100193, China
| | - Xue Yang
- College of Food Science and Engineering, Gansu Agricultural University, Lanzhou 730070, China
| | - Xiaoli Yang
- Gansu Institute of Business and Technology, Lanzhou 730010, China
| | - Hao Zhang
- Department of Nutrition and Health, China Agricultural University, Beijing 100193, China
| | - Pengjie Wang
- Department of Nutrition and Health, China Agricultural University, Beijing 100193, China
| | - Juan Song
- College of Food Science and Engineering, Gansu Agricultural University, Lanzhou 730070, China
| | - Longlin Wang
- College of Food Science and Engineering, Gansu Agricultural University, Lanzhou 730070, China
| | - Weibing Zhang
- College of Food Science and Engineering, Gansu Agricultural University, Lanzhou 730070, China.
| | - Pengcheng Wen
- College of Food Science and Engineering, Gansu Agricultural University, Lanzhou 730070, China.
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3
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Li X, Morel JD, Benegiamo G, Poisson J, Bachmann A, Rapin A, Sulc J, Williams E, Perino A, Schoonjans K, Bou Sleiman M, Auwerx J. Genetic and dietary modulators of the inflammatory response in the gastrointestinal tract of the BXD mouse genetic reference population. eLife 2023; 12:RP87569. [PMID: 37855835 PMCID: PMC10586803 DOI: 10.7554/elife.87569] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2023] Open
Abstract
Inflammatory gut disorders, including inflammatory bowel disease (IBD), can be impacted by dietary, environmental, and genetic factors. While the incidence of IBD is increasing worldwide, we still lack a complete understanding of the gene-by-environment interactions underlying inflammation and IBD. Here, we profiled the colon transcriptome of 52 BXD mouse strains fed with a chow or high-fat diet (HFD) and identified a subset of BXD strains that exhibit an IBD-like transcriptome signature on HFD, indicating that an interplay of genetics and diet can significantly affect intestinal inflammation. Using gene co-expression analyses, we identified modules that are enriched for IBD-dysregulated genes and found that these IBD-related modules share cis-regulatory elements that are responsive to the STAT2, SMAD3, and REL transcription factors. We used module quantitative trait locus analyses to identify genetic loci associated with the expression of these modules. Through a prioritization scheme involving systems genetics in the mouse and integration with external human datasets, we identified Muc4 and Epha6 as the top candidates mediating differences in HFD-driven intestinal inflammation. This work provides insights into the contribution of genetics and diet to IBD risk and identifies two candidate genes, MUC4 and EPHA6, that may mediate IBD susceptibility in humans.
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Affiliation(s)
- Xiaoxu Li
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de LausanneLausanneSwitzerland
| | - Jean-David Morel
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de LausanneLausanneSwitzerland
| | - Giorgia Benegiamo
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de LausanneLausanneSwitzerland
| | - Johanne Poisson
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de LausanneLausanneSwitzerland
| | - Alexis Bachmann
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de LausanneLausanneSwitzerland
| | - Alexis Rapin
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de LausanneLausanneSwitzerland
| | - Jonathan Sulc
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de LausanneLausanneSwitzerland
| | - Evan Williams
- Luxembourg Centre for Systems Biomedicine, University of LuxembourgEsch-sur-AlzetteLuxembourg
| | - Alessia Perino
- Laboratory of Metabolic Signaling, Institute of Bioengineering, École Polytechnique Fédérale de LausanneLausanneSwitzerland
| | - Kristina Schoonjans
- Laboratory of Metabolic Signaling, Institute of Bioengineering, École Polytechnique Fédérale de LausanneLausanneSwitzerland
| | - Maroun Bou Sleiman
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de LausanneLausanneSwitzerland
| | - Johan Auwerx
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de LausanneLausanneSwitzerland
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4
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Xu F, Ziebarth JD, Goeminne LJ, Gao J, Williams EG, Quarles LD, Makowski L, Cui Y, Williams RW, Auwerx J, Lu L. Gene network based analysis identifies a coexpression module involved in regulating plasma lipids with high-fat diet response. J Nutr Biochem 2023; 119:109398. [PMID: 37302664 PMCID: PMC10896179 DOI: 10.1016/j.jnutbio.2023.109398] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 05/08/2023] [Accepted: 05/30/2023] [Indexed: 06/13/2023]
Abstract
Plasma lipids are modulated by gene variants and many environmental factors, including diet-associated weight gain. However, understanding how these factors jointly interact to influence molecular networks that regulate plasma lipid levels is limited. Here, we took advantage of the BXD recombinant inbred family of mice to query weight gain as an environmental stressor on plasma lipids. Coexpression networks were examined in both nonobese and obese livers, and a network was identified that specifically responded to the obesogenic diet. This obesity-associated module was significantly associated with plasma lipid levels and enriched with genes known to have functions related to inflammation and lipid homeostasis. We identified key drivers of the module, including Cidec, Cidea, Pparg, Cd36, and Apoa4. The Pparg emerged as a potential master regulator of the module as it can directly target 19 of the top 30 hub genes. Importantly, activation of this module is causally linked to lipid metabolism in humans, as illustrated by correlation analysis and inverse-variance weighed Mendelian randomization. Our findings provide novel insights into gene-by-environment interactions for plasma lipid metabolism that may ultimately contribute to new biomarkers, better diagnostics, and improved approaches to prevent or treat dyslipidemia in patients.
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Affiliation(s)
- Fuyi Xu
- School of Pharmacy, Binzhou Medical University, Yantai, Shandong, China; Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Jesse D Ziebarth
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Ludger Je Goeminne
- Laboratory of Integrative Systems Physiology, Interfaculty Institute of Bioengineering, Lausanne, Switzerland
| | - Jun Gao
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Evan G Williams
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Leigh D Quarles
- Department of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Liza Makowski
- Department of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA; Center for Cancer Research, College of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Yan Cui
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Robert W Williams
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA; Center for Cancer Research, College of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Johan Auwerx
- Laboratory of Integrative Systems Physiology, Interfaculty Institute of Bioengineering, Lausanne, Switzerland.
| | - Lu Lu
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
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5
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Gautam J, Kumari D, Aggarwal H, Gupta SK, Kasarla SS, Sarkar S, Priya MRK, Kamboj P, Kumar Y, Dikshit M. Characterization of lipid signatures in the plasma and insulin-sensitive tissues of the C57BL/6J mice fed on obesogenic diets. Biochim Biophys Acta Mol Cell Biol Lipids 2023:159348. [PMID: 37285928 DOI: 10.1016/j.bbalip.2023.159348] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 05/23/2023] [Accepted: 05/29/2023] [Indexed: 06/09/2023]
Abstract
Diet-induced obesity mouse models are widely utilized to investigate the underlying mechanisms of dyslipidemia, glucose intolerance, insulin resistance, hepatic steatosis, and type 2 diabetes mellitus (T2DM), as well as for screening potential drug compounds. However, there is limited knowledge regarding specific signature lipids that accurately reflect dietary disorders. In this study, we aimed to identify key lipid signatures using LC/MS-based untargeted lipidomics in the plasma, liver, adipose tissue (AT), and skeletal muscle tissues (SKM) of male C57BL/6J mice that were fed chow, LFD, or obesogenic diets (HFD, HFHF, and HFCD) for a duration of 20 weeks. Furthermore, we conducted a comprehensive lipid analysis to assess similarities and differences with human lipid profiles. The mice fed obesogenic diets exhibited weight gain, glucose intolerance, elevated BMI, glucose and insulin levels, and a fatty liver, resembling characteristics of T2DM and obesity in humans. In total, we identified approximately 368 lipids in plasma, 433 in the liver, 493 in AT, and 624 in SKM. Glycerolipids displayed distinct patterns across the tissues, differing from human findings. However, changes in sphingolipids, phospholipids, and the expression of inflammatory and fibrotic genes showed similarities to reported human findings. Significantly modulated pathways in the obesogenic diet-fed groups included ceramide de novo synthesis, sphingolipid remodeling, and the carboxylesterase pathway, while lipoprotein-mediated pathways were minimally affected.
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Affiliation(s)
- Jyoti Gautam
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India
| | - Deepika Kumari
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India
| | - Hobby Aggarwal
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India
| | - Sonu Kumar Gupta
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India
| | - Siva Swapna Kasarla
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India
| | - Soumalya Sarkar
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India
| | - M R Kamla Priya
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India
| | - Parul Kamboj
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India
| | - Yashwant Kumar
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India.
| | - Madhu Dikshit
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India.
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6
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Jurrjens AW, Seldin MM, Giles C, Meikle PJ, Drew BG, Calkin AC. The potential of integrating human and mouse discovery platforms to advance our understanding of cardiometabolic diseases. eLife 2023; 12:e86139. [PMID: 37000167 PMCID: PMC10065800 DOI: 10.7554/elife.86139] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 03/15/2023] [Indexed: 04/01/2023] Open
Abstract
Cardiometabolic diseases encompass a range of interrelated conditions that arise from underlying metabolic perturbations precipitated by genetic, environmental, and lifestyle factors. While obesity, dyslipidaemia, smoking, and insulin resistance are major risk factors for cardiometabolic diseases, individuals still present in the absence of such traditional risk factors, making it difficult to determine those at greatest risk of disease. Thus, it is crucial to elucidate the genetic, environmental, and molecular underpinnings to better understand, diagnose, and treat cardiometabolic diseases. Much of this information can be garnered using systems genetics, which takes population-based approaches to investigate how genetic variance contributes to complex traits. Despite the important advances made by human genome-wide association studies (GWAS) in this space, corroboration of these findings has been hampered by limitations including the inability to control environmental influence, limited access to pertinent metabolic tissues, and often, poor classification of diseases or phenotypes. A complementary approach to human GWAS is the utilisation of model systems such as genetically diverse mouse panels to study natural genetic and phenotypic variation in a controlled environment. Here, we review mouse genetic reference panels and the opportunities they provide for the study of cardiometabolic diseases and related traits. We discuss how the post-GWAS era has prompted a shift in focus from discovery of novel genetic variants to understanding gene function. Finally, we highlight key advantages and challenges of integrating complementary genetic and multi-omics data from human and mouse populations to advance biological discovery.
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Affiliation(s)
- Aaron W Jurrjens
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
| | - Marcus M Seldin
- Department of Biological Chemistry and Center for Epigenetics and Metabolism, University of California, Irvine, Irvine, United States
| | - Corey Giles
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
- Baker Department of Cardiovascular Research Translation and Implementation, La Trobe University, Bundoora, Australia
| | - Peter J Meikle
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
- Baker Department of Cardiovascular Research Translation and Implementation, La Trobe University, Bundoora, Australia
| | - Brian G Drew
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
| | - Anna C Calkin
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
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7
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Wieder N, Fried JC, Kim C, Sidhom EH, Brown MR, Marshall JL, Arevalo C, Dvela-Levitt M, Kost-Alimova M, Sieber J, Gabriel KR, Pacheco J, Clish C, Abbasi HS, Singh S, Rutter J, Therrien M, Yoon H, Lai ZW, Baublis A, Subramanian R, Devkota R, Small J, Sreekanth V, Han M, Lim D, Carpenter AE, Flannick J, Finucane H, Haigis MC, Claussnitzer M, Sheu E, Stevens B, Wagner BK, Choudhary A, Shaw JL, Pablo JL, Greka A. FALCON systematically interrogates free fatty acid biology and identifies a novel mediator of lipotoxicity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.19.529127. [PMID: 36865221 PMCID: PMC9979987 DOI: 10.1101/2023.02.19.529127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
Cellular exposure to free fatty acids (FFA) is implicated in the pathogenesis of obesity-associated diseases. However, studies to date have assumed that a few select FFAs are representative of broad structural categories, and there are no scalable approaches to comprehensively assess the biological processes induced by exposure to diverse FFAs circulating in human plasma. Furthermore, assessing how these FFA- mediated processes interact with genetic risk for disease remains elusive. Here we report the design and implementation of FALCON (Fatty Acid Library for Comprehensive ONtologies) as an unbiased, scalable and multimodal interrogation of 61 structurally diverse FFAs. We identified a subset of lipotoxic monounsaturated fatty acids (MUFAs) with a distinct lipidomic profile associated with decreased membrane fluidity. Furthermore, we developed a new approach to prioritize genes that reflect the combined effects of exposure to harmful FFAs and genetic risk for type 2 diabetes (T2D). Importantly, we found that c-MAF inducing protein (CMIP) protects cells from exposure to FFAs by modulating Akt signaling and we validated the role of CMIP in human pancreatic beta cells. In sum, FALCON empowers the study of fundamental FFA biology and offers an integrative approach to identify much needed targets for diverse diseases associated with disordered FFA metabolism. Highlights FALCON (Fatty Acid Library for Comprehensive ONtologies) enables multimodal profiling of 61 free fatty acids (FFAs) to reveal 5 FFA clusters with distinct biological effectsFALCON is applicable to many and diverse cell typesA subset of monounsaturated FAs (MUFAs) equally or more toxic than canonical lipotoxic saturated FAs (SFAs) leads to decreased membrane fluidityNew approach prioritizes genes that represent the combined effects of environmental (FFA) exposure and genetic risk for diseaseC-Maf inducing protein (CMIP) is identified as a suppressor of FFA-induced lipotoxicity via Akt-mediated signaling.
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Affiliation(s)
- Nicolas Wieder
- Broad Institute of MIT and Harvard, Cambridge, USA
- Department of Medicine, Brigham and Women’s Hospital, Boston USA
- Harvard Medical School, Boston, USA
- Department of Neurology with Experimental Neurology, Charité, Berlin, Germany
| | - Juliana Coraor Fried
- Broad Institute of MIT and Harvard, Cambridge, USA
- Department of Medicine, Brigham and Women’s Hospital, Boston USA
- Harvard Medical School, Boston, USA
| | - Choah Kim
- Broad Institute of MIT and Harvard, Cambridge, USA
- Department of Medicine, Brigham and Women’s Hospital, Boston USA
- Harvard Medical School, Boston, USA
| | - Eriene-Heidi Sidhom
- Broad Institute of MIT and Harvard, Cambridge, USA
- Department of Medicine, Brigham and Women’s Hospital, Boston USA
- Harvard Medical School, Boston, USA
| | | | | | | | - Moran Dvela-Levitt
- Broad Institute of MIT and Harvard, Cambridge, USA
- Department of Medicine, Brigham and Women’s Hospital, Boston USA
- Harvard Medical School, Boston, USA
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel
| | | | - Jonas Sieber
- Department of Endocrinology, Metabolism and Cardiovascular Systems, University of Fribourg, Fribourg, Switzerland
| | | | | | - Clary Clish
- Broad Institute of MIT and Harvard, Cambridge, USA
| | | | | | - Justine Rutter
- Broad Institute of MIT and Harvard, Cambridge, USA
- Harvard Medical School, Boston, USA
| | | | - Haejin Yoon
- Department of Cell Biology, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Ludwig Center for Cancer Research at Harvard, Boston, MA 02115, USA
| | - Zon Weng Lai
- Harvard Chan Advanced Multiomics Platform, Harvard T.H. Chan School of Public Health, Boston MA 02115 USA
| | - Aaron Baublis
- Harvard Chan Advanced Multiomics Platform, Harvard T.H. Chan School of Public Health, Boston MA 02115 USA
| | - Renuka Subramanian
- Laboratory for Surgical and Metabolic Research, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Ranjan Devkota
- Broad Institute of MIT and Harvard, Cambridge, USA
- Chemical Biology and Therapeutics Science, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jonnell Small
- Broad Institute of MIT and Harvard, Cambridge, USA
- Harvard Medical School, Boston, USA
- Chemical Biology and Therapeutics Science, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Vedagopuram Sreekanth
- Broad Institute of MIT and Harvard, Cambridge, USA
- Divisions of Renal Medicine and Engineering, Brigham and Women’s Hospital, Boston, MA, USA
| | | | - Donghyun Lim
- Broad Institute of MIT and Harvard, Cambridge, USA
| | | | - Jason Flannick
- Broad Institute of MIT and Harvard, Cambridge, USA
- Harvard Medical School, Boston, USA
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, USA
| | - Hilary Finucane
- Broad Institute of MIT and Harvard, Cambridge, USA
- Analytic and Translational Genetics Unit, Mass General Hospital, Boston, MA, USA
| | - Marcia C. Haigis
- Broad Institute of MIT and Harvard, Cambridge, USA
- Department of Cell Biology, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Ludwig Center for Cancer Research at Harvard, Boston, MA 02115, USA
| | - Melina Claussnitzer
- Broad Institute of MIT and Harvard, Cambridge, USA
- Harvard Medical School, Boston, USA
- Metabolism Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Eric Sheu
- Laboratory for Surgical and Metabolic Research, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Beth Stevens
- Broad Institute of MIT and Harvard, Cambridge, USA
- Harvard Medical School, Boston, USA
- Boston Children’s Hospital, F.M. Kirby Neurobiology Center, Boston, MA, USA
- Howard Hughes Medical Institute, Boston, MA, USA
| | - Bridget K. Wagner
- Broad Institute of MIT and Harvard, Cambridge, USA
- Chemical Biology and Therapeutics Science, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Amit Choudhary
- Broad Institute of MIT and Harvard, Cambridge, USA
- Harvard Medical School, Boston, USA
- Chemical Biology and Therapeutics Science, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Divisions of Renal Medicine and Engineering, Brigham and Women’s Hospital, Boston, MA, USA
| | | | | | - Anna Greka
- Broad Institute of MIT and Harvard, Cambridge, USA
- Department of Medicine, Brigham and Women’s Hospital, Boston USA
- Harvard Medical School, Boston, USA
- Lead Contact
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8
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Molendijk J, Blazev R, Mills RJ, Ng YK, Watt KI, Chau D, Gregorevic P, Crouch PJ, Hilton JBW, Lisowski L, Zhang P, Reue K, Lusis AJ, Hudson JE, James DE, Seldin MM, Parker BL. Proteome-wide systems genetics identifies UFMylation as a regulator of skeletal muscle function. eLife 2022; 11:e82951. [PMID: 36472367 PMCID: PMC9833826 DOI: 10.7554/elife.82951] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 11/29/2022] [Indexed: 12/12/2022] Open
Abstract
Improving muscle function has great potential to improve the quality of life. To identify novel regulators of skeletal muscle metabolism and function, we performed a proteomic analysis of gastrocnemius muscle from 73 genetically distinct inbred mouse strains, and integrated the data with previously acquired genomics and >300 molecular/phenotypic traits via quantitative trait loci mapping and correlation network analysis. These data identified thousands of associations between protein abundance and phenotypes and can be accessed online (https://muscle.coffeeprot.com/) to identify regulators of muscle function. We used this resource to prioritize targets for a functional genomic screen in human bioengineered skeletal muscle. This identified several negative regulators of muscle function including UFC1, an E2 ligase for protein UFMylation. We show UFMylation is up-regulated in a mouse model of amyotrophic lateral sclerosis, a disease that involves muscle atrophy. Furthermore, in vivo knockdown of UFMylation increased contraction force, implicating its role as a negative regulator of skeletal muscle function.
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Affiliation(s)
- Jeffrey Molendijk
- Department of Anatomy and Physiology, University of MelbourneMelbourneAustralia
- Centre for Muscle Research, University of MelbourneMelbourneAustralia
| | - Ronnie Blazev
- Department of Anatomy and Physiology, University of MelbourneMelbourneAustralia
- Centre for Muscle Research, University of MelbourneMelbourneAustralia
| | | | - Yaan-Kit Ng
- Department of Anatomy and Physiology, University of MelbourneMelbourneAustralia
- Centre for Muscle Research, University of MelbourneMelbourneAustralia
| | - Kevin I Watt
- Department of Anatomy and Physiology, University of MelbourneMelbourneAustralia
- Centre for Muscle Research, University of MelbourneMelbourneAustralia
| | - Daryn Chau
- Department of Biological Chemistry and Center for Epigenetics and Metabolism, University of California, IrvineIrvineUnited States
| | - Paul Gregorevic
- Department of Anatomy and Physiology, University of MelbourneMelbourneAustralia
- Centre for Muscle Research, University of MelbourneMelbourneAustralia
| | - Peter J Crouch
- Department of Biochemistry and Pharmacology, University of MelbourneMelbourneAustralia
| | - James BW Hilton
- Department of Biochemistry and Pharmacology, University of MelbourneMelbourneAustralia
| | - Leszek Lisowski
- Children's Medical Research Institute, University of SydneySydneyAustralia
- Military Institute of MedicineWarszawaPoland
| | - Peixiang Zhang
- Department of Human Genetics/Medicine, David Geffen School of Medicine, University of California, Los AngelesLos AngelesUnited States
| | - Karen Reue
- Department of Human Genetics/Medicine, David Geffen School of Medicine, University of California, Los AngelesLos AngelesUnited States
| | - Aldons J Lusis
- Department of Human Genetics/Medicine, David Geffen School of Medicine, University of California, Los AngelesLos AngelesUnited States
- Department of Microbiology, Immunology and Molecular Genetics, University of California, Los AngelesLos AngelesUnited States
| | - James E Hudson
- QIMR Berghofer Medical Research InstituteBrisbaneAustralia
| | - David E James
- Charles Perkins Centre, School of Life and Environmental Science, School of Medical Science, University of SydneySydneyAustralia
| | - Marcus M Seldin
- Department of Biological Chemistry and Center for Epigenetics and Metabolism, University of California, IrvineIrvineUnited States
| | - Benjamin L Parker
- Department of Anatomy and Physiology, University of MelbourneMelbourneAustralia
- Centre for Muscle Research, University of MelbourneMelbourneAustralia
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9
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Peschel G, Grimm J, Müller M, Höring M, Krautbauer S, Weigand K, Liebisch G, Buechler C. Sex-specific changes in triglyceride profiles in liver cirrhosis and hepatitis C virus infection. Lipids Health Dis 2022; 21:106. [PMID: 36280840 PMCID: PMC9590217 DOI: 10.1186/s12944-022-01715-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 10/11/2022] [Indexed: 12/05/2022] Open
Abstract
Background Hepatitis C virus (HCV) infection is associated with serum lipid abnormalities, which partly normalize following direct-acting antiviral (DAA) therapy. Here, associations of serum triglycerides (TGs) with viral genotype and markers of liver disease severity were evaluated in patients with chronic HCV. Methods The study included the serum of 177 patients with chronic HCV. TGs were quantified by flow injection analysis Fourier transform mass spectrometry. Laboratory values and noninvasive scores for liver fibrosis assessment were determined. The nonparametric Kruskal‒Wallis test, one-way ANOVA, multiple linear regression and Student’s t test were used as appropriate. P values were adjusted for multiple comparisons. Results HCV-infected women had lower serum TGs than men, and thus, a sex-specific analysis was performed. None of the 46 TG species analyzed differed in the serum of female patients with and without liver cirrhosis. In contrast, in the serum of male patients with liver cirrhosis, TGs with 53, 56 and 58 carbon atoms and three to eight double bonds were diminished. These polyunsaturated TGs were also low in males with a high fibrosis-4 score. TGs with 7 or 8 double bonds negatively correlated with the model of end-stage liver disease score in males. In addition, TGs with 49, 51 and 53 carbon atoms were reduced in male patients infected with genotype 3a in comparison to genotype 1a. TGs with 56 carbon atoms were lower in genotype 3a-infected males than in genotype 1b-infected males. TGs did not differ in females by genotype. Genotype 3-related changes disappeared at the end of therapy with DAAs. Overall, the levels of serum TGs did not change during DAA therapy in either sex. Consequently, the serum TGs of males with liver cirrhosis were lower than those of males without cirrhosis at the end of therapy. Such a difference was not apparent in females. Conclusions The decline in TGs observed only in male patients with liver cirrhosis and male patients infected with genotype 3 illustrates sex-specific changes in lipid metabolism in chronic HCV. Supplementary Information The online version contains supplementary material available at 10.1186/s12944-022-01715-w.
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Affiliation(s)
- Georg Peschel
- grid.411941.80000 0000 9194 7179Department of Internal Medicine I, Gastroenterology, Hepatology, Endocrinology, Rheumatology and Infectious Diseases, University Hospital Regensburg, 93053 Regensburg, Germany ,Department of Internal Medicine, Klinikum Fürstenfeldbruck, 82256 Fürstenfeldbruck, Germany
| | - Jonathan Grimm
- grid.411941.80000 0000 9194 7179Department of Internal Medicine I, Gastroenterology, Hepatology, Endocrinology, Rheumatology and Infectious Diseases, University Hospital Regensburg, 93053 Regensburg, Germany
| | - Martina Müller
- grid.411941.80000 0000 9194 7179Department of Internal Medicine I, Gastroenterology, Hepatology, Endocrinology, Rheumatology and Infectious Diseases, University Hospital Regensburg, 93053 Regensburg, Germany
| | - Marcus Höring
- grid.411941.80000 0000 9194 7179Institute of Clinical Chemistry and Laboratory Medicine, Regensburg University Hospital, 93053 Regensburg, Germany
| | - Sabrina Krautbauer
- grid.411941.80000 0000 9194 7179Institute of Clinical Chemistry and Laboratory Medicine, Regensburg University Hospital, 93053 Regensburg, Germany
| | - Kilian Weigand
- grid.411941.80000 0000 9194 7179Department of Internal Medicine I, Gastroenterology, Hepatology, Endocrinology, Rheumatology and Infectious Diseases, University Hospital Regensburg, 93053 Regensburg, Germany ,grid.502406.50000 0004 0559 328XDepartment of Gastroenterology, Gemeinschaftsklinikum Mittelrhein, 56073 Koblenz, Germany
| | - Gerhard Liebisch
- grid.411941.80000 0000 9194 7179Institute of Clinical Chemistry and Laboratory Medicine, Regensburg University Hospital, 93053 Regensburg, Germany
| | - Christa Buechler
- grid.411941.80000 0000 9194 7179Department of Internal Medicine I, Gastroenterology, Hepatology, Endocrinology, Rheumatology and Infectious Diseases, University Hospital Regensburg, 93053 Regensburg, Germany
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10
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Li H, Perino A, Huang Q, Von Alvensleben GVG, Banaei-Esfahani A, Velazquez-Villegas LA, Gariani K, Korbelius M, Bou Sleiman M, Imbach J, Sun Y, Li X, Bachmann A, Goeminne LJE, Gallart-Ayala H, Williams EG, Ivanisevic J, Auwerx J, Schoonjans K. Integrative systems analysis identifies genetic and dietary modulators of bile acid homeostasis. Cell Metab 2022; 34:1594-1610.e4. [PMID: 36099916 PMCID: PMC9534359 DOI: 10.1016/j.cmet.2022.08.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 06/22/2022] [Accepted: 08/16/2022] [Indexed: 11/16/2022]
Abstract
Bile acids (BAs) are complex and incompletely understood enterohepatic-derived hormones that control whole-body metabolism. Here, we profiled postprandial BAs in the liver, feces, and plasma of 360 chow- or high-fat-diet-fed BXD male mice and demonstrated that both genetics and diet strongly influence BA abundance, composition, and correlation with metabolic traits. Through an integrated systems approach, we mapped hundreds of quantitative trait loci that modulate BAs and identified both known and unknown regulators of BA homeostasis. In particular, we discovered carboxylesterase 1c (Ces1c) as a genetic determinant of plasma tauroursodeoxycholic acid (TUDCA), a BA species with established disease-preventing actions. The association between Ces1c and plasma TUDCA was validated using data from independent mouse cohorts and a Ces1c knockout mouse model. Collectively, our data are a unique resource to dissect the physiological importance of BAs as determinants of metabolic traits, as underscored by the identification of CES1C as a master regulator of plasma TUDCA levels.
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Affiliation(s)
- Hao Li
- Laboratory of Metabolic Signaling, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland; Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Alessia Perino
- Laboratory of Metabolic Signaling, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Qingyao Huang
- Laboratory of Metabolic Signaling, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Giacomo V G Von Alvensleben
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Amir Banaei-Esfahani
- Laboratory of Metabolic Signaling, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Laura A Velazquez-Villegas
- Laboratory of Metabolic Signaling, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Karim Gariani
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Melanie Korbelius
- Laboratory of Metabolic Signaling, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Maroun Bou Sleiman
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Jéromine Imbach
- Laboratory of Metabolic Signaling, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Yu Sun
- Laboratory of Metabolic Signaling, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Xiaoxu Li
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Alexis Bachmann
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Ludger J E Goeminne
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Hector Gallart-Ayala
- Metabolomics Platform, Faculty of Biology and Medicine, University of Lausanne, 1005 Lausanne, Switzerland
| | - Evan G Williams
- Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Julijana Ivanisevic
- Metabolomics Platform, Faculty of Biology and Medicine, University of Lausanne, 1005 Lausanne, Switzerland
| | - Johan Auwerx
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.
| | - Kristina Schoonjans
- Laboratory of Metabolic Signaling, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.
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11
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Benegiamo G, Bou Sleiman M, Wohlwend M, Rodríguez-López S, Goeminne LJE, Laurila PP, Klevjer M, Salonen MK, Lahti J, Jha P, Cogliati S, Enriquez JA, Brumpton BM, Bye A, Eriksson JG, Auwerx J. COX7A2L genetic variants determine cardiorespiratory fitness in mice and human. Nat Metab 2022; 4:1336-1351. [PMID: 36253618 PMCID: PMC9584823 DOI: 10.1038/s42255-022-00655-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 09/06/2022] [Indexed: 01/20/2023]
Abstract
Mitochondrial respiratory complexes form superassembled structures called supercomplexes. COX7A2L is a supercomplex-specific assembly factor in mammals, although its implication for supercomplex formation and cellular metabolism remains controversial. Here we identify a role for COX7A2L for mitochondrial supercomplex formation in humans. By using human cis-expression quantitative trait loci data, we highlight genetic variants in the COX7A2L gene that affect its skeletal muscle expression specifically. The most significant cis-expression quantitative trait locus is a 10-bp insertion in the COX7A2L 3' untranslated region that increases messenger RNA stability and expression. Human myotubes harboring this insertion have more supercomplexes and increased respiration. Notably, increased COX7A2L expression in the muscle is associated with lower body fat and improved cardiorespiratory fitness in humans. Accordingly, specific reconstitution of Cox7a2l expression in C57BL/6J mice leads to higher maximal oxygen consumption, increased lean mass and increased energy expenditure. Furthermore, Cox7a2l expression in mice is induced specifically in the muscle upon exercise. These findings elucidate the genetic basis of mitochondrial supercomplex formation and function in humans and show that COX7A2L plays an important role in cardiorespiratory fitness, which could have broad therapeutic implications in reducing cardiovascular mortality.
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Affiliation(s)
- Giorgia Benegiamo
- Laboratory of Integrative Systems Physiology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Maroun Bou Sleiman
- Laboratory of Integrative Systems Physiology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Martin Wohlwend
- Laboratory of Integrative Systems Physiology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Sandra Rodríguez-López
- Laboratory of Integrative Systems Physiology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Ludger J E Goeminne
- Laboratory of Integrative Systems Physiology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Pirkka-Pekka Laurila
- Laboratory of Integrative Systems Physiology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Marie Klevjer
- Cardiac Exercise Research Group (CERG), Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Cardiology, St Olav's Hospital, Trondheim, Norway
| | - Minna K Salonen
- Finnish Institute for Health and Welfare, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
| | - Jari Lahti
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
- Turku Institute for Advanced Studies, University of Turku, Turku, Finland
| | - Pooja Jha
- Laboratory of Integrative Systems Physiology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Sara Cogliati
- Centro Nacional de Investigaciones Cardiovasculares Carlos III, Madrid, Spain
- Centro de Biología Molecular Severo Ochoa (CBMSO) & Institute for Molecular Biology-IUBM, Consejo Superior de Investigaciones Científicas-Universidad Autónoma de Madrid (CSIC-UAM), Madrid, Spain
- Instituto Universitario de Biología Molecular - IUBM (Universidad Autónoma de Madrid), Madrid, Spain
| | - José Antonio Enriquez
- Centro Nacional de Investigaciones Cardiovasculares Carlos III, Madrid, Spain
- Centro de Investigaciones Biomedicas en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Ben M Brumpton
- Clinic of Medicine, St Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU Norwegian University of Science and Technology, Trondheim, Norway
| | - Anja Bye
- Cardiac Exercise Research Group (CERG), Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Cardiology, St Olav's Hospital, Trondheim, Norway
| | - Johan G Eriksson
- Folkhälsan Research Center, Helsinki, Finland
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
| | - Johan Auwerx
- Laboratory of Integrative Systems Physiology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
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12
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Lipid biosynthesis enzyme Agpat5 in AgRP-neurons is required for insulin-induced hypoglycemia sensing and glucagon secretion. Nat Commun 2022; 13:5761. [PMID: 36180454 PMCID: PMC9525695 DOI: 10.1038/s41467-022-33484-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 09/21/2022] [Indexed: 11/13/2022] Open
Abstract
The counterregulatory response to hypoglycemia that restores normal blood glucose levels is an essential physiological function. It is initiated, in large part, by incompletely characterized brain hypoglycemia sensing neurons that trigger the secretion of counterregulatory hormones, in particular glucagon, to stimulate hepatic glucose production. In a genetic screen of recombinant inbred BXD mice we previously identified Agpat5 as a candidate regulator of hypoglycemia-induced glucagon secretion. Here, using genetic mouse models, we demonstrate that Agpat5 expressed in agouti-related peptide neurons is required for their activation by hypoglycemia, for hypoglycemia-induced vagal nerve activity, and glucagon secretion. We find that inactivation of Agpat5 leads to increased fatty acid oxidation and ATP production and that suppressing Cpt1a-dependent fatty acid import into mitochondria restores hypoglycemia sensing. Collectively, our data show that AgRP neurons are involved in the control of glucagon secretion and that Agpat5, by partitioning fatty acyl-CoAs away from mitochondrial fatty acid oxidation and ATP generation, ensures that the fall in intracellular ATP, which triggers neuronal firing, faithfully reflects changes in glycemia. During hypoglycemia, glucagon secretion is part of the mechanism needed to restore normal blood glucose levels. Here, Strembitska et al. report that sensing of hypoglycemia by AgRP neurons requires Agpat5, an enzyme which prevents fatty acids from entering the mitochondria for ATP production, ensuring correct neuronal activation and glucagon secretion.
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13
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Garikapati V, Colasante C, Baumgart-Vogt E, Spengler B. Sequential lipidomic, metabolomic, and proteomic analyses of serum, liver, and heart tissue specimens from peroxisomal biogenesis factor 11α knockout mice. Anal Bioanal Chem 2022; 414:2235-2250. [PMID: 35083512 PMCID: PMC8821073 DOI: 10.1007/s00216-021-03860-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 11/25/2021] [Accepted: 12/20/2021] [Indexed: 12/16/2022]
Abstract
Peroxisomes are versatile single membrane-enclosed cytoplasmic organelles, involved in reactive oxygen species (ROS) and lipid metabolism and diverse other metabolic processes. Peroxisomal disorders result from mutations in Pex genes-encoded proteins named peroxins (PEX proteins) and single peroxisomal enzyme deficiencies. The PEX11 protein family (α, β, and γ isoforms) plays an important role in peroxisomal proliferation and fission. However, their specific functions and the metabolic impact caused by their deficiencies have not been precisely characterized. To understand the systemic molecular alterations caused by peroxisomal defects, here we utilized untreated peroxisomal biogenesis factor 11α knockout (Pex11α KO) mouse model and performed serial relative-quantitative lipidomic, metabolomic, and proteomic analyses of serum, liver, and heart tissue homogenates. We demonstrated significant specific changes in the abundances of multiple lipid species, polar metabolites, and proteins and dysregulated metabolic pathways in distinct biological specimens of the Pex11α KO adult mice in comparison to the wild type (WT) controls. Overall, the present study reports comprehensive semi-quantitative molecular omics information of the Pex11α KO mice, which might serve in the future as a reference for a better understanding of the roles of Pex11α and underlying pathophysiological mechanisms of peroxisomal biogenesis disorders.
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Affiliation(s)
- Vannuruswamy Garikapati
- Institute of Inorganic and Analytical Chemistry, Justus Liebig University Giessen, 35392, Giessen, Germany.,Institute for Anatomy and Cell Biology II, Division of Medical Cell Biology, Justus Liebig University Giessen, 35392, Giessen, Germany
| | - Claudia Colasante
- Institute for Anatomy and Cell Biology II, Division of Medical Cell Biology, Justus Liebig University Giessen, 35392, Giessen, Germany
| | - Eveline Baumgart-Vogt
- Institute for Anatomy and Cell Biology II, Division of Medical Cell Biology, Justus Liebig University Giessen, 35392, Giessen, Germany.
| | - Bernhard Spengler
- Institute of Inorganic and Analytical Chemistry, Justus Liebig University Giessen, 35392, Giessen, Germany.
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14
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Fuchs CD, Radun R, Dixon ED, Mlitz V, Timelthaler G, Halilbasic E, Herac M, Jonker JW, Ronda OAHO, Tardelli M, Haemmerle G, Zimmermann R, Scharnagl H, Stojakovic T, Verkade HJ, Trauner M. Hepatocyte-specific deletion of adipose triglyceride lipase (adipose triglyceride lipase/patatin-like phospholipase domain containing 2) ameliorates dietary induced steatohepatitis in mice. Hepatology 2022; 75:125-139. [PMID: 34387896 DOI: 10.1002/hep.32112] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 07/29/2021] [Accepted: 08/11/2021] [Indexed: 12/18/2022]
Abstract
BACKGROUND AND AIMS Increased fatty acid (FA) flux from adipose tissue to the liver contributes to the development of NAFLD. Because free FAs are key lipotoxic triggers accelerating disease progression, inhibiting adipose triglyceride lipase (ATGL)/patatin-like phospholipase domain containing 2 (PNPLA2), the main enzyme driving lipolysis, may attenuate steatohepatitis. APPROACH AND RESULTS Hepatocyte-specific ATGL knockout (ATGL LKO) mice were challenged with methionine-choline-deficient (MCD) or high-fat high-carbohydrate (HFHC) diet. Serum biochemistry, hepatic lipid content and liver histology were assessed. Mechanistically, hepatic gene and protein expression of lipid metabolism, inflammation, fibrosis, apoptosis, and endoplasmic reticulum (ER) stress markers were investigated. DNA binding activity for peroxisome proliferator-activated receptor (PPAR) α and PPARδ was measured. After short hairpin RNA-mediated ATGL knockdown, HepG2 cells were treated with lipopolysaccharide (LPS) or oleic acid:palmitic acid 2:1 (OP21) to explore the direct role of ATGL in inflammation in vitro. On MCD and HFHC challenge, ATGL LKO mice showed reduced PPARα and increased PPARδ DNA binding activity when compared with challenged wild-type (WT) mice. Despite histologically and biochemically pronounced hepatic steatosis, dietary-challenged ATGL LKO mice showed lower hepatic inflammation, reflected by the reduced number of Galectin3/MAC-2 and myeloperoxidase-positive cells and low mRNA expression levels of inflammatory markers (such as IL-1β and F4/80) when compared with WT mice. In line with this, protein levels of the ER stress markers protein kinase R-like endoplasmic reticulum kinase and inositol-requiring enzyme 1α were reduced in ATGL LKO mice fed with MCD diet. Accordingly, pretreatment of LPS-treated HepG2 cells with the PPARδ agonist GW0742 suppressed mRNA expression of inflammatory markers. Additionally, ATGL knockdown in HepG2 cells attenuated LPS/OP21-induced expression of proinflammatory cytokines and chemokines such as chemokine (C-X-C motif) ligand 5, chemokine (C-C motif) ligand (Ccl) 2, and Ccl5. CONCLUSIONS Low hepatic lipolysis and increased PPARδ activity in ATGL/PNPLA2 deficiency may counteract hepatic inflammation and ER stress despite increased steatosis. Therefore, lowering hepatocyte lipolysis through ATGL inhibition represents a promising therapeutic strategy for the treatment of steatohepatitis.
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Affiliation(s)
- Claudia D Fuchs
- Hans Popper Laboratory of Molecular Hepatology, Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Richard Radun
- Hans Popper Laboratory of Molecular Hepatology, Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Emmanuel D Dixon
- Hans Popper Laboratory of Molecular Hepatology, Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Veronika Mlitz
- Hans Popper Laboratory of Molecular Hepatology, Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Gerald Timelthaler
- Institute for Cancer Research, Internal Medicine I, Medical University of Vienna, Vienna, Austria
| | - Emina Halilbasic
- Hans Popper Laboratory of Molecular Hepatology, Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Merima Herac
- Clinical Institute of Pathology, Medical University Vienna, Vienna, Austria
| | - Johan W Jonker
- Department of Pediatrics, Section of Molecular Metabolism and Nutrition, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Onne A H O Ronda
- Pediatric Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Matteo Tardelli
- Hans Popper Laboratory of Molecular Hepatology, Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria.,Division of Gastroenterology and Hepatology, Department of Medicine, Weill Cornell Medical College, New York, New York, USA
| | - Guenter Haemmerle
- BioTechMed-Graz, Graz, Austria.,Institute of Molecular Biosciences, University of Graz, Graz, Austria
| | - Robert Zimmermann
- BioTechMed-Graz, Graz, Austria.,Institute of Molecular Biosciences, University of Graz, Graz, Austria
| | - Hubert Scharnagl
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Tatjana Stojakovic
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, University Hospital Graz, Graz, Austria
| | - Henkjan J Verkade
- Pediatric Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Michael Trauner
- Hans Popper Laboratory of Molecular Hepatology, Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
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15
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Rivas Serna IM, Sitina M, Stokin GB, Medina-Inojosa JR, Lopez-Jimenez F, Gonzalez-Rivas JP, Vinciguerra M. Lipidomic Profiling Identifies Signatures of Poor Cardiovascular Health. Metabolites 2021; 11:metabo11110747. [PMID: 34822405 PMCID: PMC8624456 DOI: 10.3390/metabo11110747] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Revised: 10/26/2021] [Accepted: 10/27/2021] [Indexed: 12/31/2022] Open
Abstract
Ideal cardiovascular health (CVH) is defined for the presence of ideal behavioral and health metrics known to prevent cardiovascular disease (CVD). The association of circulatory phospho- and sphingo-lipids to primary reduction in cardiovascular risk is unclear. Our aim was to determine the association of CVH metrics with the circulating lipid profile of a population-based cohort. Serum sphingolipid and phospholipid species were extracted from 461 patients of the randomly selected prospective Kardiovize study based on Brno, Czech Republic. Lipids species were measured by a hyphenated mass spectrometry technique, and were associated with poor CVH scores, as defined by the American Heart Association. Phosphatidylcholine (PC), phosphatidylethanolamine (PE), lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE) species were significantly lower in ideal and intermediate scores of health dietary metric, blood pressure, total cholesterol and blood fasting glucose compared to poor scores. Current smokers presented higher levels of PC, PE and LPE individual species compared to non-smokers. Ceramide (Cer) d18:1/14:0 was altered in poor blood pressure, total cholesterol and fasting blood glucose metrics. Poor cardiovascular health metric is associated with a specific phospho- and sphingolipid pattern. Circulatory lipid profiling is a potential biomarker to refine cardiovascular health status in primary prevention strategies.
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Affiliation(s)
- Irma Magaly Rivas Serna
- International Clinical Research Center (ICRC), St Anne’s University Hospital, 53, 656 91 Brno, Czech Republic; (I.M.R.S.); (M.S.); (G.B.S.); (J.P.G.-R.)
| | - Michal Sitina
- International Clinical Research Center (ICRC), St Anne’s University Hospital, 53, 656 91 Brno, Czech Republic; (I.M.R.S.); (M.S.); (G.B.S.); (J.P.G.-R.)
| | - Gorazd B. Stokin
- International Clinical Research Center (ICRC), St Anne’s University Hospital, 53, 656 91 Brno, Czech Republic; (I.M.R.S.); (M.S.); (G.B.S.); (J.P.G.-R.)
| | - Jose R. Medina-Inojosa
- Division of Preventive Cardiology, Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55902, USA; (J.R.M.-I.); (F.L.-J.)
- Marriot Heart Disease Research Program, Rochester, MN 55902, USA
| | - Francisco Lopez-Jimenez
- Division of Preventive Cardiology, Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55902, USA; (J.R.M.-I.); (F.L.-J.)
| | - Juan P. Gonzalez-Rivas
- International Clinical Research Center (ICRC), St Anne’s University Hospital, 53, 656 91 Brno, Czech Republic; (I.M.R.S.); (M.S.); (G.B.S.); (J.P.G.-R.)
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Manlio Vinciguerra
- International Clinical Research Center (ICRC), St Anne’s University Hospital, 53, 656 91 Brno, Czech Republic; (I.M.R.S.); (M.S.); (G.B.S.); (J.P.G.-R.)
- Correspondence:
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16
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Harshfield EL, Fauman EB, Stacey D, Paul DS, Ziemek D, Ong RMY, Danesh J, Butterworth AS, Rasheed A, Sattar T, Zameer-Ul-Asar, Saleem I, Hina Z, Ishtiaq U, Qamar N, Mallick NH, Yaqub Z, Saghir T, Rizvi SNH, Memon A, Ishaq M, Rasheed SZ, Memon FUR, Jalal A, Abbas S, Frossard P, Saleheen D, Wood AM, Griffin JL, Koulman A. Genome-wide analysis of blood lipid metabolites in over 5000 South Asians reveals biological insights at cardiometabolic disease loci. BMC Med 2021; 19:232. [PMID: 34503513 PMCID: PMC8431908 DOI: 10.1186/s12916-021-02087-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 08/04/2021] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Genetic, lifestyle, and environmental factors can lead to perturbations in circulating lipid levels and increase the risk of cardiovascular and metabolic diseases. However, how changes in individual lipid species contribute to disease risk is often unclear. Moreover, little is known about the role of lipids on cardiovascular disease in Pakistan, a population historically underrepresented in cardiovascular studies. METHODS We characterised the genetic architecture of the human blood lipidome in 5662 hospital controls from the Pakistan Risk of Myocardial Infarction Study (PROMIS) and 13,814 healthy British blood donors from the INTERVAL study. We applied a candidate causal gene prioritisation tool to link the genetic variants associated with each lipid to the most likely causal genes, and Gaussian Graphical Modelling network analysis to identify and illustrate relationships between lipids and genetic loci. RESULTS We identified 253 genetic associations with 181 lipids measured using direct infusion high-resolution mass spectrometry in PROMIS, and 502 genetic associations with 244 lipids in INTERVAL. Our analyses revealed new biological insights at genetic loci associated with cardiometabolic diseases, including novel lipid associations at the LPL, MBOAT7, LIPC, APOE-C1-C2-C4, SGPP1, and SPTLC3 loci. CONCLUSIONS Our findings, generated using a distinctive lipidomics platform in an understudied South Asian population, strengthen and expand the knowledge base of the genetic determinants of lipids and their association with cardiometabolic disease-related loci.
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Affiliation(s)
- Eric L Harshfield
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK. .,Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK.
| | - Eric B Fauman
- Internal Medicine Research Unit, Pfizer Worldwide Research, Development and Medical, Cambridge, Massachusetts, 02139, USA
| | - David Stacey
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Dirk S Paul
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK.,British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, CB2 0QQ, UK.,National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, CB1 8RN, UK.,National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, CB2 0QQ, UK.,Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, CB10 1SA, UK.,Department of Human Genetics, Wellcome Sanger Institute, Hinxton, CB10 1SA, UK
| | - Daniel Ziemek
- Inflammation and Immunology, Pfizer Worldwide Research, Development and Medical, 10785, Berlin, Germany
| | - Rachel M Y Ong
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - John Danesh
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK.,British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, CB2 0QQ, UK.,National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, CB1 8RN, UK.,National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, CB2 0QQ, UK.,Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, CB10 1SA, UK.,Department of Human Genetics, Wellcome Sanger Institute, Hinxton, CB10 1SA, UK
| | - Adam S Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK.,British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, CB2 0QQ, UK.,National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, CB1 8RN, UK.,National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, CB2 0QQ, UK.,Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, CB10 1SA, UK.,Department of Human Genetics, Wellcome Sanger Institute, Hinxton, CB10 1SA, UK
| | - Asif Rasheed
- Center for Non-Communicable Diseases, Karachi, 75300, Pakistan
| | - Taniya Sattar
- Center for Non-Communicable Diseases, Karachi, 75300, Pakistan
| | - Zameer-Ul-Asar
- Center for Non-Communicable Diseases, Karachi, 75300, Pakistan
| | - Imran Saleem
- Center for Non-Communicable Diseases, Karachi, 75300, Pakistan
| | - Zoubia Hina
- Center for Non-Communicable Diseases, Karachi, 75300, Pakistan
| | - Unzila Ishtiaq
- Center for Non-Communicable Diseases, Karachi, 75300, Pakistan
| | - Nadeem Qamar
- National Institute of Cardiovascular Diseases, Karachi, 75510, Pakistan
| | | | - Zia Yaqub
- National Institute of Cardiovascular Diseases, Karachi, 75510, Pakistan
| | - Tahir Saghir
- National Institute of Cardiovascular Diseases, Karachi, 75510, Pakistan
| | | | - Anis Memon
- National Institute of Cardiovascular Diseases, Karachi, 75510, Pakistan
| | - Mohammad Ishaq
- Karachi Institute of Heart Diseases, Karachi, 75950, Pakistan
| | | | | | - Anjum Jalal
- Faisalabad Institute of Cardiology, Faisalabad, 38000, Pakistan
| | - Shahid Abbas
- Faisalabad Institute of Cardiology, Faisalabad, 38000, Pakistan
| | | | - Danish Saleheen
- Center for Non-Communicable Diseases, Karachi, 75300, Pakistan.,Department of Biostatistics & Epidemiology, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
| | - Angela M Wood
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK.,British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, CB2 0QQ, UK.,National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, CB1 8RN, UK.,National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, CB2 0QQ, UK.,Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, CB10 1SA, UK.,Department of Human Genetics, Wellcome Sanger Institute, Hinxton, CB10 1SA, UK
| | - Julian L Griffin
- Department of Biochemistry and Cambridge Systems Biology Centre, University of Cambridge, Cambridge, CB2 1GA, UK. .,Section of Biomolecular Medicine, Division of Systems Medicine, Department of Metabolism, Digestion, and Reproduction, Imperial College London, London, SW7 2AZ, UK.
| | - Albert Koulman
- Core Metabolomics and Lipidomics Laboratory, National Institute for Health Research, Cambridge Biomedical Research Centre, Cambridge, CB2 0QQ, UK.
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17
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Roy S, Sleiman MB, Jha P, Ingels JF, Chapman CJ, McCarty MS, Ziebarth JD, Hook M, Sun A, Zhao W, Huang J, Neuner SM, Wilmott LA, Shapaker TM, Centeno AG, Ashbrook DG, Mulligan MK, Kaczorowski CC, Makowski L, Cui Y, Read RW, Miller RA, Mozhui K, Williams EG, Sen S, Lu L, Auwerx J, Williams RW. Gene-by-environment modulation of lifespan and weight gain in the murine BXD family. Nat Metab 2021; 3:1217-1227. [PMID: 34552269 PMCID: PMC8478125 DOI: 10.1038/s42255-021-00449-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 08/06/2021] [Indexed: 02/07/2023]
Abstract
How lifespan and body weight vary as a function of diet and genetic differences is not well understood. Here we quantify the impact of differences in diet on lifespan in a genetically diverse family of female mice, split into matched isogenic cohorts fed a low-fat chow diet (CD, n = 663) or a high-fat diet (HFD, n = 685). We further generate key metabolic data in a parallel cohort euthanized at four time points. HFD feeding shortens lifespan by 12%: equivalent to a decade in humans. Initial body weight and early weight gains account for longevity differences of roughly 4-6 days per gram. At 500 days, animals on a HFD typically gain four times as much weight as control, but variation in weight gain does not correlate with lifespan. Classic serum metabolites, often regarded as health biomarkers, are not necessarily strong predictors of longevity. Our data indicate that responses to a HFD are substantially modulated by gene-by-environment interactions, highlighting the importance of genetic variation in making accurate individualized dietary recommendations.
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Affiliation(s)
- Suheeta Roy
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - Maroun Bou Sleiman
- Laboratory of Integrative Systems Physiology, Interfaculty Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Pooja Jha
- Laboratory of Integrative Systems Physiology, Interfaculty Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jesse F Ingels
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - Casey J Chapman
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - Melinda S McCarty
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - Jesse D Ziebarth
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - Michael Hook
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - Anna Sun
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - Wenyuan Zhao
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - Jinsong Huang
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - Sarah M Neuner
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - Lynda A Wilmott
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - Thomas M Shapaker
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - Arthur G Centeno
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - David G Ashbrook
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - Megan K Mulligan
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | | | - Liza Makowski
- Department of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Yan Cui
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - Robert W Read
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - Richard A Miller
- Department of Pathology, University of Michigan Geriatrics Center, Ann Arbor, MI, USA
| | - Khyobeni Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Evan G Williams
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Saunak Sen
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Lu Lu
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA
| | - Johan Auwerx
- Laboratory of Integrative Systems Physiology, Interfaculty Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC), Memphis, TN, USA.
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18
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Tang S, Fan L, Cheng H, Yan X. Incorporating Electro-Epoxidation into Electrospray Ionization Mass Spectrometry for Simultaneous Analysis of Negatively and Positively Charged Unsaturated Glycerophospholipids. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2021; 32:2288-2295. [PMID: 33232136 DOI: 10.1021/jasms.0c00356] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
In this study, we develop an alternating current (AC)-induced electro-epoxidation reaction and incorporate it into nanoelectrospray ionization for locating carbon-carbon double-bonds in positively and negatively charged forms of lipids simultaneously. An AC voltage plays multiple roles in this method, including initiation of the electro-epoxidation of carbon-carbon double-bonds in both charged states of lipids and protonation/deprotonation of lipids for detection in both ion modes. Moreover, the rapid switch between native lipids and their electro-epoxidation products can be achieved at different AC voltages. The efficacy of the present method was demonstrated in mixtures of lipid standards and in a biological polar lipid extract. The advantages of simultaneous detection of negatively and positively charged unsaturated lipids, the low sample consumption, and on-demand electro-epoxidation should allow its wide applications in lipid-related research.
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Affiliation(s)
- Shuli Tang
- Department of Chemistry, Texas A&M University, 580 Ross Street, College Station, Texas 77845, United States
| | - Licheng Fan
- Department of Chemistry, Texas A&M University, 580 Ross Street, College Station, Texas 77845, United States
| | - Heyong Cheng
- Department of Chemistry, Texas A&M University, 580 Ross Street, College Station, Texas 77845, United States
| | - Xin Yan
- Department of Chemistry, Texas A&M University, 580 Ross Street, College Station, Texas 77845, United States
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19
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Folick A, Koliwad SK, Valdearcos M. Microglial Lipid Biology in the Hypothalamic Regulation of Metabolic Homeostasis. Front Endocrinol (Lausanne) 2021; 12:668396. [PMID: 34122343 PMCID: PMC8191416 DOI: 10.3389/fendo.2021.668396] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 05/05/2021] [Indexed: 12/18/2022] Open
Abstract
In mammals, myeloid cells help maintain the homeostasis of peripheral metabolic tissues, and their immunologic dysregulation contributes to the progression of obesity and associated metabolic disease. There is accumulating evidence that innate immune cells also serve as functional regulators within the mediobasal hypothalamus (MBH), a critical brain region controlling both energy and glucose homeostasis. Specifically, microglia, the resident parenchymal myeloid cells of the CNS, play important roles in brain physiology and pathology. Recent studies have revealed an expanding array of microglial functions beyond their established roles as immune sentinels, including roles in brain development, circuit refinement, and synaptic organization. We showed that microglia modulate MBH function by transmitting information resulting from excess nutrient consumption. For instance, microglia can sense the excessive consumption of saturated fats and instruct neurons within the MBH accordingly, leading to responsive alterations in energy balance. Interestingly, the recent emergence of high-resolution single-cell techniques has enabled specific microglial populations and phenotypes to be profiled in unprecedented detail. Such techniques have highlighted specific subsets of microglia notable for their capacity to regulate the expression of lipid metabolic genes, including lipoprotein lipase (LPL), apolipoprotein E (APOE) and Triggering Receptor Expressed on Myeloid Cells 2 (TREM2). The discovery of this transcriptional signature highlights microglial lipid metabolism as a determinant of brain health and disease pathogenesis, with intriguing implications for the treatment of brain disorders and potentially metabolic disease. Here we review our current understanding of how changes in microglial lipid metabolism could influence the hypothalamic control of systemic metabolism.
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Affiliation(s)
- Andrew Folick
- Diabetes Center, University of California, San Francisco, San Francisco, CA, United States
- Department of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Suneil K. Koliwad
- Diabetes Center, University of California, San Francisco, San Francisco, CA, United States
- Department of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Martin Valdearcos
- Diabetes Center, University of California, San Francisco, San Francisco, CA, United States
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20
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Senevirathna JDM, Asakawa S. Multi-Omics Approaches and Radiation on Lipid Metabolism in Toothed Whales. Life (Basel) 2021; 11:364. [PMID: 33923876 PMCID: PMC8074237 DOI: 10.3390/life11040364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Revised: 04/09/2021] [Accepted: 04/17/2021] [Indexed: 11/25/2022] Open
Abstract
Lipid synthesis pathways of toothed whales have evolved since their movement from the terrestrial to marine environment. The synthesis and function of these endogenous lipids and affecting factors are still little understood. In this review, we focused on different omics approaches and techniques to investigate lipid metabolism and radiation impacts on lipids in toothed whales. The selected literature was screened, and capacities, possibilities, and future approaches for identifying unusual lipid synthesis pathways by omics were evaluated. Omics approaches were categorized into the four major disciplines: lipidomics, transcriptomics, genomics, and proteomics. Genomics and transcriptomics can together identify genes related to unique lipid synthesis. As lipids interact with proteins in the animal body, lipidomics, and proteomics can correlate by creating lipid-binding proteome maps to elucidate metabolism pathways. In lipidomics studies, recent mass spectroscopic methods can address lipid profiles; however, the determination of structures of lipids are challenging. As an environmental stress, the acoustic radiation has a significant effect on the alteration of lipid profiles. Radiation studies in different omics approaches revealed the necessity of multi-omics applications. This review concluded that a combination of many of the omics areas may elucidate the metabolism of lipids and possible hazards on lipids in toothed whales by radiation.
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Affiliation(s)
- Jayan D. M. Senevirathna
- Laboratory of Aquatic Molecular Biology and Biotechnology, Department of Aquatic Bioscience, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan;
- Department of Animal Science, Faculty of Animal Science and Export Agriculture, Uva Wellassa University, Badulla 90000, Sri Lanka
| | - Shuichi Asakawa
- Laboratory of Aquatic Molecular Biology and Biotechnology, Department of Aquatic Bioscience, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan;
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21
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Rosso N, Stephenson AM, Giraudi PJ, Tiribelli C. Diagnostic management of nonalcoholic fatty liver disease: a transformational period in the development of diagnostic and predictive tools-a narrative review. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:727. [PMID: 33987425 PMCID: PMC8106012 DOI: 10.21037/atm-20-4723] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
NAFLD is an emerging healthcare epidemic that is causing predictable adverse consequences for healthcare systems, societies and individuals. Whilst NAFLD is recognized as a multi-system disease with compound pathways that are both benign and pernicious in their unfolding; NASH is generally understood as a deleterious follow-on condition with path-specific tendencies that progress to cirrhosis, HCC and liver transplantation. Recent evidence is beginning to challenge this interpretation demanding more attention to the personalized nature of the disease and its pathogenesis across multiple different cohorts. This means that we need better diagnostic and prognostic tools not only to capture those 'at risk' disease phenotypes; but for better stratification and monitoring of patients according to their treatment strategies. With the advent of pipeline therapies for NASH underway, the medical profession looks to adopt more accurate non-invasive diagnostic tools that can help to delineate and eliminate NASH histology. This review looks at the search for the killer application revealing this particular moment in time as a transformational period; one that is pushing the boundaries of technology to integrate diverse panels of species through sensitive profiling and multi-omics approaches that cast wide, yet powerful diagnostic nets that have the potential to elucidate pathway specific biomarkers that are personalized and predictable.
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Affiliation(s)
- Natalia Rosso
- Fondazione Italiana Fegato, ONLUS Area Science Park Basovizza, Trieste, Italy
| | - Adam M Stephenson
- Helena Biosciences, Queensway South, Team Valley Trading Estate, Gateshead, UK
| | - Pablo J Giraudi
- Fondazione Italiana Fegato, ONLUS Area Science Park Basovizza, Trieste, Italy
| | - Claudio Tiribelli
- Fondazione Italiana Fegato, ONLUS Area Science Park Basovizza, Trieste, Italy
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22
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Ashbrook DG, Arends D, Prins P, Mulligan MK, Roy S, Williams EG, Lutz CM, Valenzuela A, Bohl CJ, Ingels JF, McCarty MS, Centeno AG, Hager R, Auwerx J, Lu L, Williams RW. A platform for experimental precision medicine: The extended BXD mouse family. Cell Syst 2021; 12:235-247.e9. [PMID: 33472028 PMCID: PMC7979527 DOI: 10.1016/j.cels.2020.12.002] [Citation(s) in RCA: 92] [Impact Index Per Article: 30.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 08/29/2020] [Accepted: 12/21/2020] [Indexed: 12/17/2022]
Abstract
The challenge of precision medicine is to model complex interactions among DNA variants, phenotypes, development, environments, and treatments. We address this challenge by expanding the BXD family of mice to 140 fully isogenic strains, creating a uniquely powerful model for precision medicine. This family segregates for 6 million common DNA variants-a level that exceeds many human populations. Because each member can be replicated, heritable traits can be mapped with high power and precision. Current BXD phenomes are unsurpassed in coverage and include much omics data and thousands of quantitative traits. BXDs can be extended by a single-generation cross to as many as 19,460 isogenic F1 progeny, and this extended BXD family is an effective platform for testing causal modeling and for predictive validation. BXDs are a unique core resource for the field of experimental precision medicine.
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Affiliation(s)
- David G Ashbrook
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA.
| | - Danny Arends
- Lebenswissenschaftliche Fakultät, Albrecht Daniel Thaer-Institut, Humboldt-Universität zu Berlin, Invalidenstraße 42, 10115 Berlin, Germany
| | - Pjotr Prins
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Megan K Mulligan
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Suheeta Roy
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Evan G Williams
- Luxembourg Centre for Systems Biomedicine, Université du Luxembourg, L-4365 Esch-sur-Alzette, Luxembourg
| | - Cathleen M Lutz
- Mouse Repository and the Rare and Orphan Disease Center, the Jackson Laboratory, Bar Harbor, ME 04609, USA
| | - Alicia Valenzuela
- Mouse Repository and the Rare and Orphan Disease Center, the Jackson Laboratory, Bar Harbor, ME 04609, USA
| | - Casey J Bohl
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Jesse F Ingels
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Melinda S McCarty
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Arthur G Centeno
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Reinmar Hager
- Division of Evolution & Genomic Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Oxford Road, Manchester M13 9PL, UK
| | - Johan Auwerx
- Laboratory of Integrative Systems Physiology, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Lu Lu
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA.
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA.
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23
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Tabassum R, Ripatti S. Integrating lipidomics and genomics: emerging tools to understand cardiovascular diseases. Cell Mol Life Sci 2021; 78:2565-2584. [PMID: 33449144 PMCID: PMC8004487 DOI: 10.1007/s00018-020-03715-4] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 11/09/2020] [Accepted: 11/16/2020] [Indexed: 02/07/2023]
Abstract
Cardiovascular diseases (CVDs) are the leading cause of mortality and morbidity worldwide leading to 31% of all global deaths. Early prediction and prevention could greatly reduce the enormous socio-economic burden posed by CVDs. Plasma lipids have been at the center stage of the prediction and prevention strategies for CVDs that have mostly relied on traditional lipids (total cholesterol, total triglycerides, HDL-C and LDL-C). The tremendous advancement in the field of lipidomics in last two decades has facilitated the research efforts to unravel the metabolic dysregulation in CVDs and their genetic determinants, enabling the understanding of pathophysiological mechanisms and identification of predictive biomarkers, beyond traditional lipids. This review presents an overview of the application of lipidomics in epidemiological and genetic studies and their contributions to the current understanding of the field. We review findings of these studies and discuss examples that demonstrates the potential of lipidomics in revealing new biology not captured by traditional lipids and lipoprotein measurements. The promising findings from these studies have raised new opportunities in the fields of personalized and predictive medicine for CVDs. The review further discusses prospects of integrating emerging genomics tools with the high-dimensional lipidome to move forward from the statistical associations towards biological understanding, therapeutic target development and risk prediction. We believe that integrating genomics with lipidome holds a great potential but further advancements in statistical and computational tools are needed to handle the high-dimensional and correlated lipidome.
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Affiliation(s)
- Rubina Tabassum
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, PO Box 20, 00014, Helsinki, Finland.
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, PO Box 20, 00014, Helsinki, Finland.
- Department of Public Health, Clinicum, University of Helsinki, Helsinki, Finland.
- Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA.
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24
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Norheim F, Chella Krishnan K, Bjellaas T, Vergnes L, Pan C, Parks BW, Meng Y, Lang J, Ward JA, Reue K, Mehrabian M, Gundersen TE, Péterfy M, Dalen KT, Drevon CA, Hui ST, Lusis AJ, Seldin MM. Genetic regulation of liver lipids in a mouse model of insulin resistance and hepatic steatosis. Mol Syst Biol 2021; 17:e9684. [PMID: 33417276 PMCID: PMC7792507 DOI: 10.15252/msb.20209684] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 10/31/2020] [Accepted: 11/10/2020] [Indexed: 12/12/2022] Open
Abstract
To elucidate the contributions of specific lipid species to metabolic traits, we integrated global hepatic lipid data with other omics measures and genetic data from a cohort of about 100 diverse inbred strains of mice fed a high-fat/high-sucrose diet for 8 weeks. Association mapping, correlation, structure analyses, and network modeling revealed pathways and genes underlying these interactions. In particular, our studies lead to the identification of Ifi203 and Map2k6 as regulators of hepatic phosphatidylcholine homeostasis and triacylglycerol accumulation, respectively. Our analyses highlight mechanisms for how genetic variation in hepatic lipidome can be linked to physiological and molecular phenotypes, such as microbiota composition.
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Affiliation(s)
- Frode Norheim
- Division of CardiologyDepartment of MedicineUniversity of California at Los AngelesLos AngelesCAUSA
- Department of NutritionInstitute of Basic Medical SciencesFaculty of MedicineUniversity of OsloOsloNorway
| | | | | | - Laurent Vergnes
- Department of Human GeneticsUniversity of California at Los AngelesLos AngelesCAUSA
| | - Calvin Pan
- Division of CardiologyDepartment of MedicineUniversity of California at Los AngelesLos AngelesCAUSA
| | - Brian W Parks
- Department of Nutritional SciencesUniversity of Wisconsin‐MadisonMadisonWIUSA
| | - Yonghong Meng
- Division of CardiologyDepartment of MedicineUniversity of California at Los AngelesLos AngelesCAUSA
| | - Jennifer Lang
- Division of CardiologyDepartment of MedicineUniversity of California at Los AngelesLos AngelesCAUSA
| | - James A Ward
- Division of CardiologyDepartment of MedicineUniversity of California at Los AngelesLos AngelesCAUSA
| | - Karen Reue
- Department of Human GeneticsUniversity of California at Los AngelesLos AngelesCAUSA
| | - Margarete Mehrabian
- Division of CardiologyDepartment of MedicineUniversity of California at Los AngelesLos AngelesCAUSA
| | | | - Miklós Péterfy
- Division of CardiologyDepartment of MedicineUniversity of California at Los AngelesLos AngelesCAUSA
- Depatrment of Basic Medical SciencesWestern University of Health SciencesPomonaCAUSA
| | - Knut T Dalen
- Department of NutritionInstitute of Basic Medical SciencesFaculty of MedicineUniversity of OsloOsloNorway
| | - Christian A Drevon
- Department of NutritionInstitute of Basic Medical SciencesFaculty of MedicineUniversity of OsloOsloNorway
- Vitas ASOsloNorway
| | - Simon T Hui
- Division of CardiologyDepartment of MedicineUniversity of California at Los AngelesLos AngelesCAUSA
| | - Aldons J Lusis
- Division of CardiologyDepartment of MedicineUniversity of California at Los AngelesLos AngelesCAUSA
- Department of Human GeneticsUniversity of California at Los AngelesLos AngelesCAUSA
| | - Marcus M Seldin
- Division of CardiologyDepartment of MedicineUniversity of California at Los AngelesLos AngelesCAUSA
- Department of Biological Chemistry and Center for Epigenetics and MetabolismUniversity of California, IrvineIrvineCAUSA
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25
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Genetics of Polygenic Metabolic Liver Disease. SYSTEMS MEDICINE 2021. [DOI: 10.1016/b978-0-12-801238-3.11596-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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26
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Mann JP, Pietzner M, Wittemans LB, Rolfe EDL, Kerrison ND, Imamura F, Forouhi NG, Fauman E, Allison ME, Griffin JL, Koulman A, Wareham NJ, Langenberg C. Insights into genetic variants associated with NASH-fibrosis from metabolite profiling. Hum Mol Genet 2020; 29:3451-3463. [PMID: 32720691 PMCID: PMC7116726 DOI: 10.1093/hmg/ddaa162] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Revised: 06/15/2020] [Accepted: 07/16/2020] [Indexed: 12/16/2022] Open
Abstract
Several genetic discoveries robustly implicate five single-nucleotide variants in the progression of non-alcoholic fatty liver disease to non-alcoholic steatohepatitis and fibrosis (NASH-fibrosis), including a recently identified variant in MTARC1. To better understand these variants as potential therapeutic targets, we aimed to characterize their impact on metabolism using comprehensive metabolomics data from two population-based studies. A total of 9135 participants from the Fenland study and 9902 participants from the EPIC-Norfolk cohort were included in the study. We identified individuals with risk alleles associated with NASH-fibrosis: rs738409C>G in PNPLA3, rs58542926C>T in TM6SF2, rs641738C>T near MBOAT7, rs72613567TA>T in HSD17B13 and rs2642438A>G in MTARC1. Circulating levels of 1449 metabolites were measured using targeted and untargeted metabolomics. Associations between NASH-fibrosis variants and metabolites were assessed using linear regression. The specificity of variant-metabolite associations were compared to metabolite associations with ultrasound-defined steatosis, gene variants linked to liver fat (in GCKR, PPP1R3B and LYPLAL1) and gene variants linked to cirrhosis (in HFE and SERPINA1). Each NASH-fibrosis variant demonstrated a specific metabolite profile with little overlap (8/97 metabolites) comprising diverse aspects of lipid metabolism. Risk alleles in PNPLA3 and HSD17B13 were both associated with higher 3-methylglutarylcarnitine and three variants were associated with lower lysophosphatidylcholine C14:0. The risk allele in MTARC1 was associated with higher levels of sphingomyelins. There was no overlap with metabolites that associated with HFE or SERPINA1 variants. Our results suggest a link between the NASH-protective variant in MTARC1 to the metabolism of sphingomyelins and identify distinct molecular patterns associated with each of the NASH-fibrosis variants under investigation.
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Affiliation(s)
- Jake P Mann
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0SL, UK
| | - Maik Pietzner
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0SL, UK
| | - Laura B Wittemans
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0SL, UK
| | - Emmanuela De Lucia Rolfe
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0SL, UK
| | - Nicola D Kerrison
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0SL, UK
| | - Fumiaki Imamura
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0SL, UK
| | - Nita G Forouhi
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0SL, UK
| | - Eric Fauman
- Internal Medicine Research Unit, Pfizer Worldwide Research, Development and Medical, Cambridge, MA 02142, USA
| | - Michael E Allison
- Liver Unit, Department of Medicine, Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK
| | - Jules L Griffin
- MRC Human Nutrition Research, University of Cambridge, Cambridge CB1 9NL, UK
- Department of Biochemistry, Cambridge Systems Biology Centre, University of Cambridge, Cambridge CB2 1GA, UK
| | - Albert Koulman
- MRC Human Nutrition Research, University of Cambridge, Cambridge CB1 9NL, UK
- Department of Biochemistry, Cambridge Systems Biology Centre, University of Cambridge, Cambridge CB2 1GA, UK
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0SL, UK
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0SL, UK
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27
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Dai Y, Pracana R, Holland PWH. Divergent genes in gerbils: prevalence, relation to GC-biased substitution, and phenotypic relevance. BMC Evol Biol 2020; 20:134. [PMID: 33076817 PMCID: PMC7574485 DOI: 10.1186/s12862-020-01696-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 09/29/2020] [Indexed: 11/25/2022] Open
Abstract
Background Two gerbil species, sand rat (Psammomys obesus) and Mongolian jird (Meriones unguiculatus), can become obese and show signs of metabolic dysregulation when maintained on standard laboratory diets. The genetic basis of this phenotype is unknown. Recently, genome sequencing has uncovered very unusual regions of high guanine and cytosine (GC) content scattered across the sand rat genome, most likely generated by extreme and localized biased gene conversion. A key pancreatic transcription factor PDX1 is encoded by a gene in the most extreme GC-rich region, is remarkably divergent and exhibits altered biochemical properties. Here, we ask if gerbils have proteins in addition to PDX1 that are aberrantly divergent in amino acid sequence, whether they have also become divergent due to GC-biased nucleotide changes, and whether these proteins could plausibly be connected to metabolic dysfunction exhibited by gerbils. Results We analyzed ~ 10,000 proteins with 1-to-1 orthologues in human and rodents and identified 50 proteins that accumulated unusually high levels of amino acid change in the sand rat and 41 in Mongolian jird. We show that more than half of the aberrantly divergent proteins are associated with GC biased nucleotide change and many are in previously defined high GC regions. We highlight four aberrantly divergent gerbil proteins, PDX1, INSR, MEDAG and SPP1, that may plausibly be associated with dietary metabolism. Conclusions We show that through the course of gerbil evolution, many aberrantly divergent proteins have accumulated in the gerbil lineage, and GC-biased nucleotide substitution rather than positive selection is the likely cause of extreme divergence in more than half of these. Some proteins carry putatively deleterious changes that could be associated with metabolic and physiological phenotypes observed in some gerbil species. We propose that these animals provide a useful model to study the ‘tug-of-war’ between natural selection and the excessive accumulation of deleterious substitutions mutations through biased gene conversion.
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Affiliation(s)
- Yichen Dai
- Department of Zoology, University of Oxford, 11a Mansfield Road, Oxford, OX1 3SZ, UK
| | - Rodrigo Pracana
- Department of Zoology, University of Oxford, 11a Mansfield Road, Oxford, OX1 3SZ, UK
| | - Peter W H Holland
- Department of Zoology, University of Oxford, 11a Mansfield Road, Oxford, OX1 3SZ, UK.
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28
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Brademan DR, Miller IJ, Kwiecien NW, Pagliarini DJ, Westphall MS, Coon JJ, Shishkova E. Argonaut: A Web Platform for Collaborative Multi-omic Data Visualization and Exploration. PATTERNS (NEW YORK, N.Y.) 2020; 1:100122. [PMID: 33154995 PMCID: PMC7641515 DOI: 10.1016/j.patter.2020.100122] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 08/15/2020] [Accepted: 09/14/2020] [Indexed: 12/12/2022]
Abstract
Researchers now generate large multi-omic datasets using increasingly mature mass spectrometry techniques at an astounding pace, facing new challenges of "Big Data" dissemination, visualization, and exploration. Conveniently, web-based data portals accommodate the complexity of multi-omic experiments and the many experts involved. However, developing these tailored companion resources requires programming expertise and knowledge of web server architecture-a substantial burden for most. Here, we describe Argonaut, a simple, code-free, and user-friendly platform for creating customizable, interactive data-hosting websites. Argonaut carries out real-time statistical analyses of the data, which it organizes into easily sharable projects. Collaborating researchers worldwide can explore the results, visualized through popular plots, and modify them to streamline data interpretation. Increasing the pace and ease of access to multi-omic data, Argonaut aims to propel discovery of new biological insights. We showcase the capabilities of this tool using a published multi-omics dataset on the large mitochondrial protease deletion collection.
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Affiliation(s)
- Dain R. Brademan
- Department of Chemistry, University of Wisconsin–Madison, Madison, WI 53706, USA
- Morgridge Institute for Research, Madison, WI 53715, USA
| | - Ian J. Miller
- Department of Biomolecular Chemistry, University of Wisconsin–Madison, Madison, WI 53706, USA
| | - Nicholas W. Kwiecien
- Department of Chemistry, University of Wisconsin–Madison, Madison, WI 53706, USA
| | - David J. Pagliarini
- Morgridge Institute for Research, Madison, WI 53715, USA
- Department of Biomolecular Chemistry, University of Wisconsin–Madison, Madison, WI 53706, USA
- Department of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Michael S. Westphall
- Department of Biomolecular Chemistry, University of Wisconsin–Madison, Madison, WI 53706, USA
| | - Joshua J. Coon
- Department of Chemistry, University of Wisconsin–Madison, Madison, WI 53706, USA
- Morgridge Institute for Research, Madison, WI 53715, USA
- Department of Biomolecular Chemistry, University of Wisconsin–Madison, Madison, WI 53706, USA
| | - Evgenia Shishkova
- Department of Biomolecular Chemistry, University of Wisconsin–Madison, Madison, WI 53706, USA
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29
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Linke V, Overmyer KA, Miller IJ, Brademan DR, Hutchins PD, Trujillo EA, Reddy TR, Russell JD, Cushing EM, Schueler KL, Stapleton DS, Rabaglia ME, Keller MP, Gatti DM, Keele GR, Pham D, Broman KW, Churchill GA, Attie AD, Coon JJ. A large-scale genome-lipid association map guides lipid identification. Nat Metab 2020; 2:1149-1162. [PMID: 32958938 PMCID: PMC7572687 DOI: 10.1038/s42255-020-00278-3] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 08/11/2020] [Indexed: 12/13/2022]
Abstract
Despite the crucial roles of lipids in metabolism, we are still at the early stages of comprehensively annotating lipid species and their genetic basis. Mass spectrometry-based discovery lipidomics offers the potential to globally survey lipids and their relative abundances in various biological samples. To discover the genetics of lipid features obtained through high-resolution liquid chromatography-tandem mass spectrometry, we analysed liver and plasma from 384 diversity outbred mice, and quantified 3,283 molecular features. These features were mapped to 5,622 lipid quantitative trait loci and compiled into a public web resource termed LipidGenie. The data are cross-referenced to the human genome and offer a bridge between genetic associations in humans and mice. Harnessing this resource, we used genome-lipid association data as an additional aid to identify a number of lipids, for example gangliosides through their association with B4galnt1, and found evidence for a group of sex-specific phosphatidylcholines through their shared locus. Finally, LipidGenie's ability to query either mass or gene-centric terms suggests acyl-chain-specific functions for proteins of the ABHD family.
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Affiliation(s)
- Vanessa Linke
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Katherine A Overmyer
- Morgridge Institute for Research, Madison, WI, USA
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Ian J Miller
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Dain R Brademan
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Paul D Hutchins
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Edna A Trujillo
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Thiru R Reddy
- Morgridge Institute for Research, Madison, WI, USA
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | | | - Emily M Cushing
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Kathryn L Schueler
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Donald S Stapleton
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Mary E Rabaglia
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Mark P Keller
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
| | | | | | - Duy Pham
- The Jackson Laboratory, Bar Harbor, ME, USA
| | - Karl W Broman
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
| | | | - Alan D Attie
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Joshua J Coon
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA.
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI, USA.
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30
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Sun T, Wang X, Cong P, Xu J, Xue C. Mass spectrometry-based lipidomics in food science and nutritional health: A comprehensive review. Compr Rev Food Sci Food Saf 2020; 19:2530-2558. [PMID: 33336980 DOI: 10.1111/1541-4337.12603] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2020] [Revised: 05/14/2020] [Accepted: 06/10/2020] [Indexed: 12/16/2022]
Abstract
With the advance in science and technology as well as the improvement of living standards, the function of food is no longer just to meet the needs of survival. Food science and its associated nutritional health issues have been increasingly debated. Lipids, as complex metabolites, play a key role both in food and human health. Taking advantages of mass spectrometry (MS) by combining its high sensitivity and accuracy with extensive selective determination of all lipid classes, MS-based lipidomics has been employed to resolve the conundrum of addressing both qualitative and quantitative aspects of high-abundance and low-abundance lipids in complex food matrices. In this review, we systematically summarize current applications of MS-based lipidomics in food field. First, common MS-based lipidomics procedures are described. Second, the applications of MS-based lipidomics in food science, including lipid composition characterization, adulteration, traceability, and other issues, are discussed. Third, the application of MS-based lipidomics for nutritional health covering the influence of food on health and disease is introduced. Finally, future research trends and challenges are proposed. MS-based lipidomics plays an important role in the field of food science, promoting continuous development of food science and integration of food knowledge with other disciplines. New methods of MS-based lipidomics have been developed to improve accuracy and sensitivity of lipid analysis in food samples. These developments offer the possibility to fully characterize lipids in food samples, identify novel functional lipids, and better understand the role of food in promoting healt.
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Affiliation(s)
- Tong Sun
- College of Food Science and Engineering, Ocean University of China, Qingdao, China
| | - Xincen Wang
- College of Food Science and Engineering, Ocean University of China, Qingdao, China
| | - Peixu Cong
- College of Food Science and Engineering, Ocean University of China, Qingdao, China
| | - Jie Xu
- College of Food Science and Engineering, Ocean University of China, Qingdao, China
| | - Changhu Xue
- College of Food Science and Engineering, Ocean University of China, Qingdao, China.,Qingdao National Laboratory for Marine Science and Technology, Laboratory of Marine Drugs & Biological Products, Qingdao, China
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31
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Li M, Li Q, Kang S, Cao X, Zheng Y, Wu J, Wu R, Shao J, Yang M, Yue X. Characterization and comparison of lipids in bovine colostrum and mature milk based on UHPLC-QTOF-MS lipidomics. Food Res Int 2020; 136:109490. [PMID: 32846571 DOI: 10.1016/j.foodres.2020.109490] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2019] [Revised: 06/17/2020] [Accepted: 06/23/2020] [Indexed: 12/30/2022]
Abstract
Lipids in bovine milk have several biological activities, with implications for human health and the physical functionality of foods. However, alterations in the lipid profile of bovine milk during lactation are not well-studied. This study aimed to identify differences in lipids between bovine colostrum and mature milk, using a lipidomics approach. Using an advanced mass spectrometry-based quantitative lipidomics approach, 335 lipids assigned to 13 subclasses were characterized in bovine colostrum (BC) and mature milk (BM). In total, 63 significantly differential lipids (SDLs) were identified. Among the 63 SDLs, the levels of 21 lipids were significantly lower in BM than in BC, including 5 glycerophosphatidylethanolamines (PEs), 1 glycerophosphatidylglycerol (PG), and 15 triacylglycerols (TGs). The levels of the remaining 42 lipids increased in BM, including 1 cardiolipin (CL), 9 diacylglycerols (DGs), 9 dihexosylceramides (Hex2Cers), 3 hexosylceramides (HexCers), 3 glycerophosphatidic acids (PAs), 2 glycerophosphatidylcholines (PCs), 12 PEs, and 3 TGs. Furthermore, the correlations and related metabolic pathways of these 63 SDLs were analyzed to explore the mechanisms that alter bovine milk lipids during lactation. The seven most relevant pathways identified herein, ranked in accordance with their degree of influence on lactation, were glycerophospholipid metabolism, sphingolipid metabolism, glycerolipid metabolism, glycosylphosphatidylinositol-anchor biosynthesis, linoleic acid metabolism, alpha-linolenic acid metabolism, and arachidonic acid metabolism. Our results provide essential insights into mechanisms underlying alterations in bovine milk lipids during different lactation periods, along with practical information of specific nutrition and quality assessments for the dairy industry.
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Affiliation(s)
- Mohan Li
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning Province, China
| | - Qilong Li
- College of Bioscience and Biotechnology, Shenyang Agricultural University, Shenyang, Liaoning Province, China
| | - Shimo Kang
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning Province, China
| | - Xueyan Cao
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning Province, China
| | - Yan Zheng
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning Province, China
| | - Junrui Wu
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning Province, China
| | - Rina Wu
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning Province, China
| | - Junhua Shao
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning Province, China
| | - Mei Yang
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning Province, China.
| | - Xiqing Yue
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning Province, China.
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32
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Mouse Systems Genetics as a Prelude to Precision Medicine. Trends Genet 2020; 36:259-272. [PMID: 32037011 DOI: 10.1016/j.tig.2020.01.004] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 01/06/2020] [Accepted: 01/08/2020] [Indexed: 12/17/2022]
Abstract
Mouse models have been instrumental in understanding human disease biology and proposing possible new treatments. The precise control of the environment and genetic composition of mice allows more rigorous observations, but limits the generalizability and translatability of the results into human applications. In the era of precision medicine, strategies using mouse models have to be revisited to effectively emulate human populations. Systems genetics is one promising paradigm that may promote the transition to novel precision medicine strategies. Here, we review the state-of-the-art resources and discuss how mouse systems genetics helps to understand human diseases and to advance the development of precision medicine, with an emphasis on the existing resources and strategies.
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Abstract
The common forms of metabolic diseases are highly complex, involving hundreds of genes, environmental and lifestyle factors, age-related changes, sex differences and gut-microbiome interactions. Systems genetics is a population-based approach to address this complexity. In contrast to commonly used 'reductionist' approaches, such as gain or loss of function, that examine one element at a time, systems genetics uses high-throughput 'omics' technologies to quantitatively assess the many molecular differences among individuals in a population and then to relate these to physiologic functions or disease states. Unlike genome-wide association studies, systems genetics seeks to go beyond the identification of disease-causing genes to understand higher-order interactions at the molecular level. The purpose of this review is to introduce the systems genetics applications in the areas of metabolic and cardiovascular disease. Here, we explain how large clinical and omics-level data and databases from both human and animal populations are available to help researchers place genes in the context of pathways and networks and formulate hypotheses that can then be experimentally examined. We provide lists of such databases and examples of the integration of reductionist and systems genetics data. Among the important applications emerging is the development of improved nutritional and pharmacological strategies to address the rise of metabolic diseases.
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Affiliation(s)
- Marcus Seldin
- Department of Medicine, Division of Cardiology, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Biological Chemistry and Center for Epigenetics and Metabolism, University of California, Irvine, Irvine, CA, USA
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Aldons J Lusis
- Department of Medicine, Division of Cardiology, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA.
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34
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Tabassum R, Rämö JT, Ripatti P, Koskela JT, Kurki M, Karjalainen J, Palta P, Hassan S, Nunez-Fontarnau J, Kiiskinen TTJ, Söderlund S, Matikainen N, Gerl MJ, Surma MA, Klose C, Stitziel NO, Laivuori H, Havulinna AS, Service SK, Salomaa V, Pirinen M, Jauhiainen M, Daly MJ, Freimer NB, Palotie A, Taskinen MR, Simons K, Ripatti S. Genetic architecture of human plasma lipidome and its link to cardiovascular disease. Nat Commun 2019; 10:4329. [PMID: 31551469 PMCID: PMC6760179 DOI: 10.1038/s41467-019-11954-8] [Citation(s) in RCA: 98] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Accepted: 08/13/2019] [Indexed: 01/07/2023] Open
Abstract
Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P <5 ×10-8), 10 of which associate with CVD risk including five new loci-COL5A1, GLTPD2, SPTLC3, MBOAT7 and GALNT16 (false discovery rate<0.05). We identify loci for lipid species that are shown to predict CVD e.g., SPTLC3 for CER(d18:1/24:1). We show that lipoprotein lipase (LPL) may more efficiently hydrolyze medium length triacylglycerides (TAGs) than others. Polyunsaturated lipids have highest heritability and genetic correlations, suggesting considerable genetic regulation at fatty acids levels. We find low genetic correlations between traditional lipids and lipid species. Our results show that lipidomic profiles capture information beyond traditional lipids and identify genetic variants modifying lipid levels and risk of CVD.
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Affiliation(s)
- Rubina Tabassum
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Joel T Rämö
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Pietari Ripatti
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Jukka T Koskela
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Mitja Kurki
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics and Genetic Analysis Platform, Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric & Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Juha Karjalainen
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Priit Palta
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Shabbeer Hassan
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Javier Nunez-Fontarnau
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Tuomo T J Kiiskinen
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
| | - Sanni Söderlund
- Research Programs Unit, Diabetes & Obesity, University of Helsinki and Department of Internal Medicine, Helsinki University Hospital, Helsinki, Finland
| | - Niina Matikainen
- Research Programs Unit, Diabetes & Obesity, University of Helsinki and Department of Internal Medicine, Helsinki University Hospital, Helsinki, Finland
- Endocrinology, Abdominal Center, Helsinki University Hospital, Helsinki, Finland
| | | | - Michal A Surma
- Lipotype GmbH, Dresden, Germany
- Łukasiewicz Research Network-PORT Polish Center for Technology Development, Stablowicka 147 Str., 54-066, Wroclaw, Poland
| | | | - Nathan O Stitziel
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, Saint Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO, USA
- McDonnell Genome Institute, Washington University School of Medicine, Saint Louis, MO, USA
| | - Hannele Laivuori
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Obstetrics and Gynecology, Tampere University Hospital and Tampere University, Faculty of Medicine and Health Technology, Tampere, Finland
- Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Aki S Havulinna
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
| | - Susan K Service
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Veikko Salomaa
- National Institute for Health and Welfare, Helsinki, Finland
| | - Matti Pirinen
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Helsinki Institute for Information Technology HIIT and Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Matti Jauhiainen
- National Institute for Health and Welfare, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Biomedicum, Helsinki, Finland
| | - Mark J Daly
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Nelson B Freimer
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Psychiatric & Neurodevelopmental Genetics Unit, Department of Psychiatry, Analytic and Translational Genetics Unit, Department of Medicine, and the Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Marja-Riitta Taskinen
- Research Programs Unit, Diabetes & Obesity, University of Helsinki and Department of Internal Medicine, Helsinki University Hospital, Helsinki, Finland
| | - Kai Simons
- Lipotype GmbH, Dresden, Germany
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland.
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA.
- Department of Public Health, Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
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Jang C, Hui S, Zeng X, Cowan AJ, Wang L, Chen L, Morscher RJ, Reyes J, Frezza C, Hwang HY, Imai A, Saito Y, Okamoto K, Vaspoli C, Kasprenski L, Zsido GA, Gorman JH, Gorman RC, Rabinowitz JD. Metabolite Exchange between Mammalian Organs Quantified in Pigs. Cell Metab 2019; 30:594-606.e3. [PMID: 31257152 PMCID: PMC6726553 DOI: 10.1016/j.cmet.2019.06.002] [Citation(s) in RCA: 151] [Impact Index Per Article: 30.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 04/16/2019] [Accepted: 05/31/2019] [Indexed: 12/30/2022]
Abstract
Mammalian organs continually exchange metabolites via circulation, but systems-level analysis of this shuttling process is lacking. Here, we compared, in fasted pigs, metabolite concentrations in arterial blood versus draining venous blood from 11 organs. Greater than 90% of metabolites showed arterial-venous differences across at least one organ. Surprisingly, the liver and kidneys released not only glucose but also amino acids, both of which were consumed primarily by the intestine and pancreas. The liver and kidneys exhibited additional unexpected activities: liver preferentially burned unsaturated over more atherogenic saturated fatty acids, whereas the kidneys were unique in burning circulating citrate and net oxidizing lactate to pyruvate, thereby contributing to circulating redox homeostasis. Furthermore, we observed more than 700 other cases of tissue-specific metabolite production or consumption, such as release of nucleotides by the spleen and TCA intermediates by pancreas. These data constitute a high-value resource, providing a quantitative atlas of inter-organ metabolite exchange.
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Affiliation(s)
- Cholsoon Jang
- Department of Chemistry and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Sheng Hui
- Department of Chemistry and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Xianfeng Zeng
- Department of Chemistry and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Alexis J Cowan
- Department of Chemistry and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Lin Wang
- Department of Chemistry and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Li Chen
- Department of Chemistry and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Raphael J Morscher
- Department of Chemistry and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Jorge Reyes
- Department of Chemistry and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - Christian Frezza
- Medical Research Council Cancer Unit, Hutchison/MRC Research Centre, University of Cambridge, Cambridge, UK
| | - Ho Young Hwang
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Blvd, Philadelphia, PA 19104, USA
| | - Akito Imai
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Blvd, Philadelphia, PA 19104, USA
| | - Yoshiaki Saito
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Blvd, Philadelphia, PA 19104, USA
| | - Keitaro Okamoto
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Blvd, Philadelphia, PA 19104, USA
| | - Christine Vaspoli
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Blvd, Philadelphia, PA 19104, USA
| | - Loewe Kasprenski
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Blvd, Philadelphia, PA 19104, USA
| | - Gerald A Zsido
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Blvd, Philadelphia, PA 19104, USA
| | - Joseph H Gorman
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Blvd, Philadelphia, PA 19104, USA
| | - Robert C Gorman
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Blvd, Philadelphia, PA 19104, USA
| | - Joshua D Rabinowitz
- Department of Chemistry and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.
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Affiliation(s)
- Joel T Haas
- INSERM UMR1011, European Genomic Institute for Diabetes, University of Lille, CHU Lille, Institut Pasteur de Lille, Lille, France
| | - Bart Staels
- INSERM UMR1011, European Genomic Institute for Diabetes, University of Lille, CHU Lille, Institut Pasteur de Lille, Lille, France.
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37
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Parker BL, Calkin AC, Seldin MM, Keating MF, Tarling EJ, Yang P, Moody SC, Liu Y, Zerenturk EJ, Needham EJ, Miller ML, Clifford BL, Morand P, Watt MJ, Meex RCR, Peng KY, Lee R, Jayawardana K, Pan C, Mellett NA, Weir JM, Lazarus R, Lusis AJ, Meikle PJ, James DE, de Aguiar Vallim TQ, Drew BG. An integrative systems genetic analysis of mammalian lipid metabolism. Nature 2019; 567:187-193. [PMID: 30814737 PMCID: PMC6656374 DOI: 10.1038/s41586-019-0984-y] [Citation(s) in RCA: 89] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Accepted: 01/23/2019] [Indexed: 12/16/2022]
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.
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Affiliation(s)
- Benjamin L Parker
- Metabolic Systems Biology Laboratory, Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales, Australia
| | - Anna C Calkin
- Lipid Metabolism & Cardiometabolic Disease Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia.
- Central Clinical School, Department of Medicine, Monash University, Melbourne, Victoria, Australia.
| | - Marcus M Seldin
- Department of Human Genetics/Medicine, David Geffen School of Medicine, University of California Los Angeles (UCLA), Los Angeles, CA, USA
| | - Michael F Keating
- Lipid Metabolism & Cardiometabolic Disease Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
- Central Clinical School, Department of Medicine, Monash University, Melbourne, Victoria, Australia
- Molecular Metabolism & Ageing Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
| | - Elizabeth J Tarling
- Department of Medicine, Division of Cardiology, University of California Los Angeles (UCLA), Los Angeles, CA, USA
- Molecular Biology Institute, University of California Los Angeles (UCLA), Los Angeles, CA, USA
| | - Pengyi Yang
- Charles Perkins Centre, School of Mathematics and Statistics, University of Sydney, Sydney, New South Wales, Australia
| | - Sarah C Moody
- Lipid Metabolism & Cardiometabolic Disease Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
- Molecular Metabolism & Ageing Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
| | - Yingying Liu
- Lipid Metabolism & Cardiometabolic Disease Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
- Molecular Metabolism & Ageing Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
| | - Eser J Zerenturk
- Lipid Metabolism & Cardiometabolic Disease Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
- Molecular Metabolism & Ageing Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
| | - Elise J Needham
- Metabolic Systems Biology Laboratory, Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales, Australia
| | - Matthew L Miller
- Molecular Biology Institute, University of California Los Angeles (UCLA), Los Angeles, CA, USA
| | - Bethan L Clifford
- Department of Medicine, Division of Cardiology, University of California Los Angeles (UCLA), Los Angeles, CA, USA
| | - Pauline Morand
- Department of Biological Chemistry, David Geffen School of Medicine, University of California Los Angeles (UCLA), Los Angeles, CA, USA
| | - Matthew J Watt
- Department of Physiology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
| | - Ruth C R Meex
- Department of Physiology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
| | - Kang-Yu Peng
- Metabolomics Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
| | | | - Kaushala Jayawardana
- Metabolomics Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
| | - Calvin Pan
- Department of Human Genetics/Medicine, David Geffen School of Medicine, University of California Los Angeles (UCLA), Los Angeles, CA, USA
| | - Natalie A Mellett
- Metabolomics Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
| | - Jacquelyn M Weir
- Metabolomics Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
| | - Ross Lazarus
- Metabolomics Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
| | - Aldons J Lusis
- Department of Human Genetics/Medicine, David Geffen School of Medicine, University of California Los Angeles (UCLA), Los Angeles, CA, USA
| | - Peter J Meikle
- Metabolomics Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
| | - David E James
- Metabolic Systems Biology Laboratory, Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales, Australia
| | - Thomas Q de Aguiar Vallim
- Department of Medicine, Division of Cardiology, University of California Los Angeles (UCLA), Los Angeles, CA, USA.
- Molecular Biology Institute, University of California Los Angeles (UCLA), Los Angeles, CA, USA.
- Department of Biological Chemistry, David Geffen School of Medicine, University of California Los Angeles (UCLA), Los Angeles, CA, USA.
| | - Brian G Drew
- Central Clinical School, Department of Medicine, Monash University, Melbourne, Victoria, Australia.
- Molecular Metabolism & Ageing Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia.
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39
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Systems Analyses Reveal Physiological Roles and Genetic Regulators of Liver Lipid Species. Cell Syst 2018; 6:722-733.e6. [PMID: 29909277 DOI: 10.1016/j.cels.2018.05.016] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Revised: 04/24/2018] [Accepted: 05/11/2018] [Indexed: 12/11/2022]
Abstract
The genetics of individual lipid species and their relevance in disease is largely unresolved. We profiled a subset of storage, signaling, membrane, and mitochondrial liver lipids across 385 mice from 47 strains of the BXD mouse population fed chow or high-fat diet and integrated these data with complementary multi-omics datasets. We identified several lipid species and lipid clusters with specific phenotypic and molecular signatures and, in particular, cardiolipin species with signatures of healthy and fatty liver. Genetic analyses revealed quantitative trait loci for 68% of the lipids (lQTL). By multi-layered omics analyses, we show the reliability of lQTLs to uncover candidate genes that can regulate the levels of lipid species. Additionally, we identified lQTLs that mapped to genes associated with abnormal lipid metabolism in human GWASs. This work provides a foundation and resource for understanding the genetic regulation and physiological significance of lipid species.
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