1
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Motsinger-Reif AA, Reif DM, Akhtari FS, House JS, Campbell CR, Messier KP, Fargo DC, Bowen TA, Nadadur SS, Schmitt CP, Pettibone KG, Balshaw DM, Lawler CP, Newton SA, Collman GW, Miller AK, Merrick BA, Cui Y, Anchang B, Harmon QE, McAllister KA, Woychik R. Gene-environment interactions within a precision environmental health framework. CELL GENOMICS 2024; 4:100591. [PMID: 38925123 DOI: 10.1016/j.xgen.2024.100591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 03/26/2024] [Accepted: 06/02/2024] [Indexed: 06/28/2024]
Abstract
Understanding the complex interplay of genetic and environmental factors in disease etiology and the role of gene-environment interactions (GEIs) across human development stages is important. We review the state of GEI research, including challenges in measuring environmental factors and advantages of GEI analysis in understanding disease mechanisms. We discuss the evolution of GEI studies from candidate gene-environment studies to genome-wide interaction studies (GWISs) and the role of multi-omics in mediating GEI effects. We review advancements in GEI analysis methods and the importance of large-scale datasets. We also address the translation of GEI findings into precision environmental health (PEH), showcasing real-world applications in healthcare and disease prevention. Additionally, we highlight societal considerations in GEI research, including environmental justice, the return of results to participants, and data privacy. Overall, we underscore the significance of GEI for disease prediction and prevention and advocate for integrating the exposome into PEH omics studies.
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Affiliation(s)
- Alison A Motsinger-Reif
- Biostatistics and Computational Biology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, Durham, NC, USA.
| | - David M Reif
- Predictive Toxicology Branch, Division of Translational Toxicology, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Farida S Akhtari
- Biostatistics and Computational Biology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - John S House
- Biostatistics and Computational Biology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - C Ryan Campbell
- Biostatistics and Computational Biology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Kyle P Messier
- Biostatistics and Computational Biology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, Durham, NC, USA; Predictive Toxicology Branch, Division of Translational Toxicology, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - David C Fargo
- Office of the Director, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Tiffany A Bowen
- Office of the Director, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Srikanth S Nadadur
- Exposure, Response, and Technology Branch, Division of Extramural Research and Training, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Charles P Schmitt
- Office of the Scientific Director, Office of Data Science, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Kristianna G Pettibone
- Program Analysis Branch, Division of Extramural Research and Training, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - David M Balshaw
- Office of the Director, National Institute of Environmental Health Sciences, Durham, NC, USA; Division of Extramural Research and Training, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Cindy P Lawler
- Genes, Environment, and Health Branch, Division of Extramural Research and Training, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Shelia A Newton
- Office of Scientific Coordination, Planning and Evaluation, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Gwen W Collman
- Office of the Director, National Institute of Environmental Health Sciences, Durham, NC, USA; Office of Scientific Coordination, Planning and Evaluation, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Aubrey K Miller
- Office of Scientific Coordination, Planning and Evaluation, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - B Alex Merrick
- Mechanistic Toxicology Branch, Division of Translational Toxicology, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Yuxia Cui
- Exposure, Response, and Technology Branch, Division of Extramural Research and Training, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Benedict Anchang
- Biostatistics and Computational Biology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Quaker E Harmon
- Epidemiology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Kimberly A McAllister
- Genes, Environment, and Health Branch, Division of Extramural Research and Training, National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Rick Woychik
- Office of the Director, National Institute of Environmental Health Sciences, Durham, NC, USA
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2
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Oyesola O, Downie AE, Howard N, Barre RS, Kiwanuka K, Zaldana K, Chen YH, Menezes A, Lee SC, Devlin J, Mondragón-Palomino O, Souza COS, Herrmann C, Koralov SB, Cadwell K, Graham AL, Loke P. Genetic and environmental interactions contribute to immune variation in rewilded mice. Nat Immunol 2024; 25:1270-1282. [PMID: 38877178 PMCID: PMC11224019 DOI: 10.1038/s41590-024-01862-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 05/02/2024] [Indexed: 06/16/2024]
Abstract
The relative and synergistic contributions of genetics and environment to interindividual immune response variation remain unclear, despite implications in evolutionary biology and medicine. Here we quantify interactive effects of genotype and environment on immune traits by investigating C57BL/6, 129S1 and PWK/PhJ inbred mice, rewilded in an outdoor enclosure and infected with the parasite Trichuris muris. Whereas cellular composition was shaped by interactions between genotype and environment, cytokine response heterogeneity including IFNγ concentrations was primarily driven by genotype with consequence on worm burden. In addition, we show that other traits, such as expression of CD44, were explained mostly by genetics on T cells, whereas expression of CD44 on B cells was explained more by environment across all strains. Notably, genetic differences under laboratory conditions were decreased following rewilding. These results indicate that nonheritable influences interact with genetic factors to shape immune variation and parasite burden.
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Affiliation(s)
- Oyebola Oyesola
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA.
| | - Alexander E Downie
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Department of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Nina Howard
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Ramya S Barre
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Department of Microbiology, Immunology, and Molecular Genetics, University of Texas Health Sciences Center at San Antonio, San Antonio, TX, USA
| | - Kasalina Kiwanuka
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Kimberly Zaldana
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
- Department of Pathology, New York University, Grossman School of Medicine, New York, NY, USA
| | - Ying-Han Chen
- Kimmel Center for Biology and Medicine at the Skirball Institute, New York University, Grossman School of Medicine, New York, NY, USA
- Division of Gastroenterology and Hepatology, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Arthur Menezes
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
| | - Soo Ching Lee
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Joseph Devlin
- Kimmel Center for Biology and Medicine at the Skirball Institute, New York University, Grossman School of Medicine, New York, NY, USA
| | - Octavio Mondragón-Palomino
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Camila Oliveira Silva Souza
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Christin Herrmann
- Kimmel Center for Biology and Medicine at the Skirball Institute, New York University, Grossman School of Medicine, New York, NY, USA
- Division of Gastroenterology and Hepatology, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sergei B Koralov
- Department of Pathology, New York University, Grossman School of Medicine, New York, NY, USA
| | - Ken Cadwell
- Division of Gastroenterology and Hepatology, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Pathobiology, University of Pennsylvania School of Veterinary Medicine, Philadelphia, PA, USA
| | - Andrea L Graham
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.
- Santa Fe Institute, Santa Fe, NM, USA.
| | - P'ng Loke
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA.
- Department of Pathobiology, University of Pennsylvania School of Veterinary Medicine, Philadelphia, PA, USA.
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3
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de Jong TV, Pan Y, Rastas P, Munro D, Tutaj M, Akil H, Benner C, Chen D, Chitre AS, Chow W, Colonna V, Dalgard CL, Demos WM, Doris PA, Garrison E, Geurts AM, Gunturkun HM, Guryev V, Hourlier T, Howe K, Huang J, Kalbfleisch T, Kim P, Li L, Mahaffey S, Martin FJ, Mohammadi P, Ozel AB, Polesskaya O, Pravenec M, Prins P, Sebat J, Smith JR, Solberg Woods LC, Tabakoff B, Tracey A, Uliano-Silva M, Villani F, Wang H, Sharp BM, Telese F, Jiang Z, Saba L, Wang X, Murphy TD, Palmer AA, Kwitek AE, Dwinell MR, Williams RW, Li JZ, Chen H. A revamped rat reference genome improves the discovery of genetic diversity in laboratory rats. CELL GENOMICS 2024; 4:100527. [PMID: 38537634 PMCID: PMC11019364 DOI: 10.1016/j.xgen.2024.100527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 12/26/2023] [Accepted: 02/29/2024] [Indexed: 04/09/2024]
Abstract
The seventh iteration of the reference genome assembly for Rattus norvegicus-mRatBN7.2-corrects numerous misplaced segments and reduces base-level errors by approximately 9-fold and increases contiguity by 290-fold compared with its predecessor. Gene annotations are now more complete, improving the mapping precision of genomic, transcriptomic, and proteomics datasets. We jointly analyzed 163 short-read whole-genome sequencing datasets representing 120 laboratory rat strains and substrains using mRatBN7.2. We defined ∼20.0 million sequence variations, of which 18,700 are predicted to potentially impact the function of 6,677 genes. We also generated a new rat genetic map from 1,893 heterogeneous stock rats and annotated transcription start sites and alternative polyadenylation sites. The mRatBN7.2 assembly, along with the extensive analysis of genomic variations among rat strains, enhances our understanding of the rat genome, providing researchers with an expanded resource for studies involving rats.
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Affiliation(s)
- Tristan V de Jong
- Department of Pharmacology, Addiction Science, and Toxicology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Yanchao Pan
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Pasi Rastas
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | - Daniel Munro
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Department of Integrative Structural and Computational Biology, Scripps Research, San Diego, CA, USA
| | - Monika Tutaj
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, USA; Rat Genome Database, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Huda Akil
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
| | - Chris Benner
- Department of Medicine, University of California San Diego, San Diego, CA, USA
| | - Denghui Chen
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Apurva S Chitre
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - William Chow
- Tree of Life, Wellcome Sanger Institute, Cambridge, UK
| | - Vincenza Colonna
- Institute of Genetics and Biophysics, National Research Council, Naples, Italy; Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Clifton L Dalgard
- Department of Anatomy, Physiology & Genetics, The American Genome Center, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Wendy M Demos
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, USA; Rat Genome Database, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Peter A Doris
- The Brown Foundation Institute of Molecular Medicine, Center for Human Genetics, University of Texas Health Science Center, Houston, TX, USA
| | - Erik Garrison
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Aron M Geurts
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Hakan M Gunturkun
- Department of Pharmacology, Addiction Science, and Toxicology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Victor Guryev
- Genome Structure and Ageing, University of Groningen, UMC, Groningen, the Netherlands
| | - Thibaut Hourlier
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus in Hinxton, Cambridgeshire, UK
| | - Kerstin Howe
- Tree of Life, Wellcome Sanger Institute, Cambridge, UK
| | - Jun Huang
- Department of Pharmacology, Addiction Science, and Toxicology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Ted Kalbfleisch
- Gluck Equine Research Center, Department of Veterinary Science, University of Kentucky, Louisville, KY, USA
| | - Panjun Kim
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Ling Li
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA; Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Spencer Mahaffey
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Fergal J Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus in Hinxton, Cambridgeshire, UK
| | - Pejman Mohammadi
- Center for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, WA, USA; Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, USA
| | - Ayse Bilge Ozel
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Oksana Polesskaya
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Michal Pravenec
- Institute of Physiology, Czech Academy of Sciences, Prague, Czechia
| | - Pjotr Prins
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Jonathan Sebat
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Jennifer R Smith
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, USA; Rat Genome Database, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Leah C Solberg Woods
- Department of Internal Medicine, Section on Molecular Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Boris Tabakoff
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Alan Tracey
- Tree of Life, Wellcome Sanger Institute, Cambridge, UK
| | | | - Flavia Villani
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Hongyang Wang
- Department of Animal Sciences, Washington State University, Pullman, WA, USA
| | - Burt M Sharp
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Francesca Telese
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Zhihua Jiang
- Department of Animal Sciences, Washington State University, Pullman, WA, USA
| | - Laura Saba
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Xusheng Wang
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA; Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Terence D Murphy
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Anne E Kwitek
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, USA; Rat Genome Database, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Melinda R Dwinell
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, USA; Rat Genome Database, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Jun Z Li
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.
| | - Hao Chen
- Department of Pharmacology, Addiction Science, and Toxicology, University of Tennessee Health Science Center, Memphis, TN, USA.
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4
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van Gerwen J, Masson SWC, Cutler HB, Vegas AD, Potter M, Stöckli J, Madsen S, Nelson ME, Humphrey SJ, James DE. The genetic and dietary landscape of the muscle insulin signalling network. eLife 2024; 12:RP89212. [PMID: 38329473 PMCID: PMC10942587 DOI: 10.7554/elife.89212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2024] Open
Abstract
Metabolic disease is caused by a combination of genetic and environmental factors, yet few studies have examined how these factors influence signal transduction, a key mediator of metabolism. Using mass spectrometry-based phosphoproteomics, we quantified 23,126 phosphosites in skeletal muscle of five genetically distinct mouse strains in two dietary environments, with and without acute in vivo insulin stimulation. Almost half of the insulin-regulated phosphoproteome was modified by genetic background on an ordinary diet, and high-fat high-sugar feeding affected insulin signalling in a strain-dependent manner. Our data revealed coregulated subnetworks within the insulin signalling pathway, expanding our understanding of the pathway's organisation. Furthermore, associating diverse signalling responses with insulin-stimulated glucose uptake uncovered regulators of muscle insulin responsiveness, including the regulatory phosphosite S469 on Pfkfb2, a key activator of glycolysis. Finally, we confirmed the role of glycolysis in modulating insulin action in insulin resistance. Our results underscore the significance of genetics in shaping global signalling responses and their adaptability to environmental changes, emphasising the utility of studying biological diversity with phosphoproteomics to discover key regulatory mechanisms of complex traits.
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Affiliation(s)
- Julian van Gerwen
- Charles Perkins Centre, School of Life and Environmental Sciences, University of SydneySydneyAustralia
| | - Stewart WC Masson
- Charles Perkins Centre, School of Life and Environmental Sciences, University of SydneySydneyAustralia
| | - Harry B Cutler
- Charles Perkins Centre, School of Life and Environmental Sciences, University of SydneySydneyAustralia
| | - Alexis Diaz Vegas
- Charles Perkins Centre, School of Life and Environmental Sciences, University of SydneySydneyAustralia
| | - Meg Potter
- Charles Perkins Centre, School of Life and Environmental Sciences, University of SydneySydneyAustralia
| | - Jacqueline Stöckli
- Charles Perkins Centre, School of Life and Environmental Sciences, University of SydneySydneyAustralia
| | - Søren Madsen
- Charles Perkins Centre, School of Life and Environmental Sciences, University of SydneySydneyAustralia
| | - Marin E Nelson
- Charles Perkins Centre, School of Life and Environmental Sciences, University of SydneySydneyAustralia
| | - Sean J Humphrey
- Charles Perkins Centre, School of Life and Environmental Sciences, University of SydneySydneyAustralia
| | - David E James
- Charles Perkins Centre, School of Life and Environmental Sciences, University of SydneySydneyAustralia
- Faculty of Medicine and Health, University of SydneySydneyAustralia
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5
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Viesi C, Seldin M. Decoding the complexities of lipid homeostasis through a unified mouse genetic resource. J Lipid Res 2024; 65:100511. [PMID: 38286180 PMCID: PMC11004979 DOI: 10.1016/j.jlr.2024.100511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2024] Open
Affiliation(s)
- Carlos Viesi
- Department of Biological Chemistry, University of California, Irvine, USA; Center for Epigenetics and Metabolism, University of California, Irvine, USA
| | - Marcus Seldin
- Department of Biological Chemistry, University of California, Irvine, USA; Center for Epigenetics and Metabolism, University of California, Irvine, USA
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6
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Zhou M, Tamburini I, Van C, Molendijk J, Nguyen CM, Chang IYY, Johnson C, Velez LM, Cheon Y, Yeo R, Bae H, Le J, Larson N, Pulido R, Nascimento-Filho CHV, Jang C, Marazzi I, Justice J, Pannunzio N, Hevener AL, Sparks L, Kershaw EE, Nicholas D, Parker BL, Masri S, Seldin MM. Leveraging inter-individual transcriptional correlation structure to infer discrete signaling mechanisms across metabolic tissues. eLife 2024; 12:RP88863. [PMID: 38224289 PMCID: PMC10945578 DOI: 10.7554/elife.88863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2024] Open
Abstract
Inter-organ communication is a vital process to maintain physiologic homeostasis, and its dysregulation contributes to many human diseases. Given that circulating bioactive factors are stable in serum, occur naturally, and are easily assayed from blood, they present obvious focal molecules for therapeutic intervention and biomarker development. Recently, studies have shown that secreted proteins mediating inter-tissue signaling could be identified by 'brute force' surveys of all genes within RNA-sequencing measures across tissues within a population. Expanding on this intuition, we reasoned that parallel strategies could be used to understand how individual genes mediate signaling across metabolic tissues through correlative analyses of gene variation between individuals. Thus, comparison of quantitative levels of gene expression relationships between organs in a population could aid in understanding cross-organ signaling. Here, we surveyed gene-gene correlation structure across 18 metabolic tissues in 310 human individuals and 7 tissues in 103 diverse strains of mice fed a normal chow or high-fat/high-sucrose (HFHS) diet. Variation of genes such as FGF21, ADIPOQ, GCG, and IL6 showed enrichments which recapitulate experimental observations. Further, similar analyses were applied to explore both within-tissue signaling mechanisms (liver PCSK9) and genes encoding enzymes producing metabolites (adipose PNPLA2), where inter-individual correlation structure aligned with known roles for these critical metabolic pathways. Examination of sex hormone receptor correlations in mice highlighted the difference of tissue-specific variation in relationships with metabolic traits. We refer to this resource as gene-derived correlations across tissues (GD-CAT) where all tools and data are built into a web portal enabling users to perform these analyses without a single line of code (gdcat.org). This resource enables querying of any gene in any tissue to find correlated patterns of genes, cell types, pathways, and network architectures across metabolic organs.
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Affiliation(s)
- Mingqi Zhou
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Ian Tamburini
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Cassandra Van
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Jeffrey Molendijk
- Department of Anatomy and Physiology, University of MelbourneMelbourneAustralia
| | - Christy M Nguyen
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | | | - Casey Johnson
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Leandro M Velez
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Youngseo Cheon
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Reichelle Yeo
- Translational Research Institute, AdventHealthOrlandoUnited States
| | - Hosung Bae
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Johnny Le
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Natalie Larson
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Ron Pulido
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Carlos HV Nascimento-Filho
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Cholsoon Jang
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Ivan Marazzi
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Jamie Justice
- Veterans Administration Greater Los Angeles Healthcare System, Geriatric Research Education and Clinical Center (GRECC)Los AngelesUnited States
| | - Nicholas Pannunzio
- Divison of Hematology/Oncology, Department of Medicine, UC Irvine HealthIrvineUnited States
| | - Andrea L Hevener
- Department of Medicine, Division of Endocrinology, Diabetes, and Hypertension, David Geffen School of Medicine at UCLALos AngelesUnited States
- Iris Cantor-UCLA Women’s Health Research Center, David Geffen School of Medicine at UCLALos AngelesUnited States
| | - Lauren Sparks
- Translational Research Institute, AdventHealthOrlandoUnited States
| | - Erin E Kershaw
- Division of Endocrinology, Department of Medicine, University of PittsburgPittsburghUnited States
| | - Dequina Nicholas
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
- Department of Molecular Biology and Biochemistry, School of Biological Sciences, University of California IrvineIrvineUnited States
| | - Benjamin L Parker
- Department of Anatomy and Physiology, University of MelbourneMelbourneAustralia
| | - Selma Masri
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
| | - Marcus M Seldin
- Department of Biological Chemistry, UC IrvineIrvineUnited States
- Center for Epigenetics and Metabolism, UC IrvineIrvineUnited States
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7
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Christians JK, Reue K. The role of gonadal hormones and sex chromosomes in sex-dependent effects of early nutrition on metabolic health. Front Endocrinol (Lausanne) 2023; 14:1304050. [PMID: 38189044 PMCID: PMC10770830 DOI: 10.3389/fendo.2023.1304050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 12/11/2023] [Indexed: 01/09/2024] Open
Abstract
Early-life conditions such as prenatal nutrition can have long-term effects on metabolic health, and these effects may differ between males and females. Understanding the biological mechanisms underlying sex differences in the response to early-life environment will improve interventions, but few such mechanisms have been identified, and there is no overall framework for understanding sex differences. Biological sex differences may be due to chromosomal sex, gonadal sex, or interactions between the two. This review describes approaches to distinguish between the roles of chromosomal and gonadal sex, and summarizes findings regarding sex differences in metabolism. The Four Core Genotypes (FCG) mouse model allows dissociation of the sex chromosome genotype from gonadal type, whereas the XY* mouse model can be used to distinguish effects of X chromosome dosage vs the presence of the Y chromosome. Gonadectomy can be used to distinguish between organizational (permanent) and activational (reversible) effects of sex hormones. Baseline sex differences in a variety of metabolic traits are influenced by both activational and organizational effects of gonadal hormones, as well as sex chromosome complement. Thus far, these approaches have not been widely applied to examine sex-dependent effects of prenatal conditions, although a number of studies have found activational effects of estradiol to be protective against the development of hypertension following early-life adversity. Genes that escape X chromosome inactivation (XCI), such as Kdm5c, contribute to baseline sex-differences in metabolism, while Ogt, another XCI escapee, leads to sex-dependent responses to prenatal maternal stress. Genome-wide approaches to the study of sex differences include mapping genetic loci influencing metabolic traits in a sex-dependent manner. Seeking enrichment for binding sites of hormone receptors among genes showing sexually-dimorphic expression can elucidate the relative roles of hormones. Using the approaches described herein to identify mechanisms underlying sex-dependent effects of early nutrition on metabolic health may enable the identification of fundamental mechanisms and potential interventions.
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Affiliation(s)
- Julian K. Christians
- Department of Biological Sciences, Simon Fraser University, Burnaby, BC, Canada
- Centre for Cell Biology, Development and Disease, Simon Fraser University, Burnaby, BC, Canada
- British Columbia Children’s Hospital Research Institute, Vancouver, BC, Canada
- Women’s Health Research Institute, BC Women’s Hospital and Health Centre, Vancouver, BC, Canada
| | - Karen Reue
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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8
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Downie AE, Oyesola O, Barre RS, Caudron Q, Chen YH, Dennis EJ, Garnier R, Kiwanuka K, Menezes A, Navarrete DJ, Mondragón-Palomino O, Saunders JB, Tokita CK, Zaldana K, Cadwell K, Loke P, Graham AL. Spatiotemporal-social association predicts immunological similarity in rewilded mice. SCIENCE ADVANCES 2023; 9:eadh8310. [PMID: 38134275 PMCID: PMC10745690 DOI: 10.1126/sciadv.adh8310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 11/21/2023] [Indexed: 12/24/2023]
Abstract
Environmental influences on immune phenotypes are well-documented, but our understanding of which elements of the environment affect immune systems, and how, remains vague. Behaviors, including socializing with others, are central to an individual's interaction with its environment. We therefore tracked behavior of rewilded laboratory mice of three inbred strains in outdoor enclosures and examined contributions of behavior, including associations measured from spatiotemporal co-occurrences, to immune phenotypes. We found extensive variation in individual and social behavior among and within mouse strains upon rewilding. In addition, we found that the more associated two individuals were, the more similar their immune phenotypes were. Spatiotemporal association was particularly predictive of similar memory T and B cell profiles and was more influential than sibling relationships or shared infection status. These results highlight the importance of shared spatiotemporal activity patterns and/or social networks for immune phenotype and suggest potential immunological correlates of social life.
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Affiliation(s)
- Alexander E. Downie
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Oyebola Oyesola
- Laboratory of Parasitic Diseases, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Ramya S. Barre
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
- Department of Microbiology, Immunology, and Molecular Genetics, University of Texas Health Sciences Center at San Antonio, San Antonio, TX 78229, USA
| | - Quentin Caudron
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Ying-Han Chen
- Kimmel Center for Biology and Medicine at the Skirball Institute, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Emily J. Dennis
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Romain Garnier
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Kasalina Kiwanuka
- Laboratory of Parasitic Diseases, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Arthur Menezes
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Daniel J. Navarrete
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
- Department of Microbiology and Immunology, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Octavio Mondragón-Palomino
- Laboratory of Parasitic Diseases, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Jesse B. Saunders
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Christopher K. Tokita
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Kimberly Zaldana
- Laboratory of Parasitic Diseases, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
- Department of Microbiology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Ken Cadwell
- Division of Gastroenterology and Hepatology, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - P’ng Loke
- Laboratory of Parasitic Diseases, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Andrea L. Graham
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
- Santa Fe Institute, Santa Fe, NM 87501, USA
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9
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Smiriglia A, Lorito N, Serra M, Perra A, Morandi A, Kowalik MA. Sex difference in liver diseases: How preclinical models help to dissect the sex-related mechanisms sustaining NAFLD and hepatocellular carcinoma. iScience 2023; 26:108363. [PMID: 38034347 PMCID: PMC10682354 DOI: 10.1016/j.isci.2023.108363] [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] [Indexed: 12/02/2023] Open
Abstract
Only a few preclinical findings are confirmed in the clinic, posing a critical issue for clinical development. Therefore, identifying the best preclinical models can help to dissect molecular and mechanistic insights into liver disease pathogenesis while being clinically relevant. In this context, the sex relevance of most preclinical models has been only partially considered. This is particularly significant in NAFLD and HCC, which have a higher prevalence in men when compared to pre-menopause women but not to those in post-menopausal status, suggesting a role for sex hormones in the pathogenesis of the diseases. This review gathers the sex-relevant findings and the available preclinical models focusing on both in vitro and in vivo studies and discusses the potential implications and perspectives of introducing the sex effect in the selection of the best preclinical model. This is a critical aspect that would help to tailor personalized therapies based on sex.
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Affiliation(s)
- Alfredo Smiriglia
- Department of Experimental and Clinical Biomedical Sciences, University of Florence, 50134 Florence, Italy
| | - Nicla Lorito
- Department of Experimental and Clinical Biomedical Sciences, University of Florence, 50134 Florence, Italy
| | - Marina Serra
- Department of Biomedical Sciences, University of Cagliari, 09042 Monserrato, Italy
| | - Andrea Perra
- Department of Biomedical Sciences, University of Cagliari, 09042 Monserrato, Italy
| | - Andrea Morandi
- Department of Experimental and Clinical Biomedical Sciences, University of Florence, 50134 Florence, Italy
| | - Marta Anna Kowalik
- Department of Biomedical Sciences, University of Cagliari, 09042 Monserrato, Italy
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10
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Price TR, Emfinger CH, Schueler KL, King S, Nicholson R, Beck T, Yandell BS, Summers SA, Holland WL, Krauss RM, Keller MP, Attie AD. Identification of genetic drivers of plasma lipoprotein size in the Diversity Outbred mouse population. J Lipid Res 2023; 64:100471. [PMID: 37944753 PMCID: PMC10750189 DOI: 10.1016/j.jlr.2023.100471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 10/28/2023] [Accepted: 10/31/2023] [Indexed: 11/12/2023] Open
Abstract
Despite great progress in understanding lipoprotein physiology, there is still much to be learned about the genetic drivers of lipoprotein abundance, composition, and function. We used ion mobility spectrometry to survey 16 plasma lipoprotein subfractions in 500 Diversity Outbred mice maintained on a Western-style diet. We identified 21 quantitative trait loci (QTL) affecting lipoprotein abundance. To refine the QTL and link them to disease risk in humans, we asked if the human homologs of genes located at each QTL were associated with lipid traits in human genome-wide association studies. Integration of mouse QTL with human genome-wide association studies yielded candidate gene drivers for 18 of the 21 QTL. This approach enabled us to nominate the gene encoding the neutral ceramidase, Asah2, as a novel candidate driver at a QTL on chromosome 19 for large HDL particles (HDL-2b). To experimentally validate Asah2, we surveyed lipoproteins in Asah2-/- mice. Compared to wild-type mice, female Asah2-/- mice showed an increase in several lipoproteins, including HDL. Our results provide insights into the genetic regulation of circulating lipoproteins, as well as mechanisms by which lipoprotein subfractions may affect cardiovascular disease risk in humans.
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Affiliation(s)
- Tara R Price
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
| | | | - Kathryn L Schueler
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Sarah King
- School of Medicine, University of California-San Francisco, San Francisco, CA, USA
| | - Rebekah Nicholson
- Department of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, UT, USA
| | - Tim Beck
- Department of Genetics and Genome Biology, University of Leicester, Leicester, UK
| | - Brian S Yandell
- Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA
| | - Scott A Summers
- Department of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, UT, USA
| | - William L Holland
- Department of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, UT, USA
| | - Ronald M Krauss
- School of Medicine, University of California-San Francisco, San Francisco, CA, USA
| | - Mark P Keller
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Alan D Attie
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA.
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11
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Cheng J, Cheng M, Lusis AJ, Yang X. Gene Regulatory Networks in Coronary Artery Disease. Curr Atheroscler Rep 2023; 25:1013-1023. [PMID: 38008808 DOI: 10.1007/s11883-023-01170-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/09/2023] [Indexed: 11/28/2023]
Abstract
PURPOSE OF REVIEW Coronary artery disease is a complex disorder and the leading cause of mortality worldwide. As technologies for the generation of high-throughput multiomics data have advanced, gene regulatory network modeling has become an increasingly powerful tool in understanding coronary artery disease. This review summarizes recent and novel gene regulatory network tools for bulk tissue and single cell data, existing databases for network construction, and applications of gene regulatory networks in coronary artery disease. RECENT FINDINGS New gene regulatory network tools can integrate multiomics data to elucidate complex disease mechanisms at unprecedented cellular and spatial resolutions. At the same time, updates to coronary artery disease expression data in existing databases have enabled researchers to build gene regulatory networks to study novel disease mechanisms. Gene regulatory networks have proven extremely useful in understanding CAD heritability beyond what is explained by GWAS loci and in identifying mechanisms and key driver genes underlying disease onset and progression. Gene regulatory networks can holistically and comprehensively address the complex nature of coronary artery disease. In this review, we discuss key algorithmic approaches to construct gene regulatory networks and highlight state-of-the-art methods that model specific modes of gene regulation. We also explore recent applications of these tools in coronary artery disease patient data repositories to understand disease heritability and shared and distinct disease mechanisms and key driver genes across tissues, between sexes, and between species.
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Grants
- DK120342, HL148577, and HL147883 (AJL). NS111378, NS117148, HL147883 (XY) NIH HHS
- DK120342, HL148577, and HL147883 (AJL). NS111378, NS117148, HL147883 (XY) NIH HHS
- DK120342, HL148577, and HL147883 (AJL). NS111378, NS117148, HL147883 (XY) NIH HHS
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Affiliation(s)
- Jenny Cheng
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
- Molecular, Cellular and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
| | - Michael Cheng
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
| | - Aldons J Lusis
- Department of Medicine, Division of Cardiology, University of California, Los Angeles, 650 Charles E Young Drive South, Los Angeles, CA, 90095, USA.
- Departments of Human Genetics & Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, 650 Charles E. Young Drive South, Los Angeles, CA, 90095, USA.
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA.
- Molecular, Cellular and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA.
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA.
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA, 90095, USA.
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12
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Pourteymour S, Drevon CA, Dalen KT, Norheim FA. Mechanisms Behind NAFLD: a System Genetics Perspective. Curr Atheroscler Rep 2023; 25:869-878. [PMID: 37812367 DOI: 10.1007/s11883-023-01158-3] [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] [Accepted: 09/19/2023] [Indexed: 10/10/2023]
Abstract
PURPOSE OF REVIEW To summarize the key factors contributing to the onset and progress of nonalcoholic fatty liver disease (NAFLD) and put them in a system genetics context. We particularly focus on how genetic regulation of hepatic lipids contributes to NAFLD. RECENT FINDINGS NAFLD is characterized by excessive accumulation of fat in the liver. This can progress to steatohepatitis (inflammation and hepatocyte injury) and eventually, cirrhosis. The severity of NAFLD is determined by a combination of factors including obesity, insulin resistance, and lipotoxic lipids, along with genetic susceptibility. Numerous studies have been conducted on large human cohorts and mouse panels, to identify key determinants in the genome, transcriptome, proteome, lipidome, microbiome and different environmental conditions contributing to NAFLD. We review common factors contributing to NAFLD and put them in a systems genetics context. In particular, we describe how genetic regulation of liver lipids contributes to NAFLD. The combination of an unhealthy lifestyle and genetic predisposition increases the likelihood of accumulating lipotoxic specie lipids that may be one of the driving forces behind developing severe forms of NAFLD.
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Affiliation(s)
- Shirin Pourteymour
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Blindern, PO Box 1046, 0317, Oslo, Norway
| | - Christian A Drevon
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Blindern, PO Box 1046, 0317, Oslo, Norway
- Vitas Ltd. Oslo Science Park, Oslo, Norway
| | - Knut Tomas Dalen
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Blindern, PO Box 1046, 0317, Oslo, Norway
| | - Frode A Norheim
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Blindern, PO Box 1046, 0317, Oslo, Norway.
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13
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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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14
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Khan AH, Bagley JR, LaPierre N, Gonzalez-Figueroa C, Spencer TC, Choudhury M, Xiao X, Eskin E, Jentsch JD, Smith DJ. Genetic pathways regulating the longitudinal acquisition of cocaine self-administration in a panel of inbred and recombinant inbred mice. Cell Rep 2023; 42:112856. [PMID: 37481717 PMCID: PMC10530068 DOI: 10.1016/j.celrep.2023.112856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 06/06/2023] [Accepted: 07/10/2023] [Indexed: 07/25/2023] Open
Abstract
To identify addiction genes, we evaluate intravenous self-administration of cocaine or saline in 84 inbred and recombinant inbred mouse strains over 10 days. We integrate the behavior data with brain RNA-seq data from 41 strains. The self-administration of cocaine and that of saline are genetically distinct. We maximize power to map loci for cocaine intake by using a linear mixed model to account for this longitudinal phenotype while correcting for population structure. A total of 15 unique significant loci are identified in the genome-wide association study. A transcriptome-wide association study highlights the Trpv2 ion channel as a key locus for cocaine self-administration as well as identifying 17 additional genes, including Arhgef26, Slc18b1, and Slco5a1. We find numerous instances where alternate splice site selection or RNA editing altered transcript abundance. Our work emphasizes the importance of Trpv2, an ionotropic cannabinoid receptor, for the response to cocaine.
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Affiliation(s)
- Arshad H Khan
- Department of Molecular and Medical Pharmacology, Geffen School of Medicine, UCLA, Los Angeles, CA 90095, USA
| | - Jared R Bagley
- Department of Psychology, Binghamton University, Binghamton, NY, USA
| | - Nathan LaPierre
- Department of Computer Science, UCLA, Los Angeles, CA 90095, USA
| | | | - Tadeo C Spencer
- Department of Integrative Biology and Physiology, UCLA, Los Angeles, CA 90095, USA
| | - Mudra Choudhury
- Department of Integrative Biology and Physiology, UCLA, Los Angeles, CA 90095, USA
| | - Xinshu Xiao
- Department of Integrative Biology and Physiology, UCLA, Los Angeles, CA 90095, USA
| | - Eleazar Eskin
- Department of Computational Medicine, UCLA, Los Angeles, CA 90095, USA
| | - James D Jentsch
- Department of Psychology, Binghamton University, Binghamton, NY, USA
| | - Desmond J Smith
- Department of Molecular and Medical Pharmacology, Geffen School of Medicine, UCLA, Los Angeles, CA 90095, USA.
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15
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Kim M, Huda MN, Evans LW, Que E, Gertz ER, Maeda-Smithies N, Bennett BJ. Integrative analysis of hepatic transcriptional profiles reveals genetic regulation of atherosclerosis in hyperlipidemic Diversity Outbred-F1 mice. Sci Rep 2023; 13:9475. [PMID: 37301941 PMCID: PMC10257719 DOI: 10.1038/s41598-023-35917-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 05/25/2023] [Indexed: 06/12/2023] Open
Abstract
Atherogenesis is an insipidus but precipitating process leading to serious consequences of many cardiovascular diseases (CVD). Numerous genetic loci contributing to atherosclerosis have been identified in human genome-wide association studies, but these studies have limitations in the ability to control environmental factors and to decipher cause/effect relationships. To assess the power of hyperlipidemic Diversity Outbred (DO) mice in facilitating quantitative trait loci (QTL) analysis of complex traits, we generated a high-resolution genetic panel of atherosclerosis susceptible (DO-F1) mouse cohort by crossing 200 DO females with C57BL/6J males carrying two human genes: encoding apolipoprotein E3-Leiden and cholesterol ester transfer protein. We examined atherosclerotic traits including plasma lipids and glucose in the 235 female and 226 male progeny before and after 16 weeks of a high-fat/cholesterol diet, and aortic plaque size at 24 weeks. We also assessed the liver transcriptome using RNA-sequencing. Our QTL mapping for atherosclerotic traits identified one previously reported female-specific QTL on Chr10 with a narrower interval of 22.73 to 30.80 Mb, and one novel male-specific QTL at 31.89 to 40.25 Mb on Chr19. Liver transcription levels of several genes within each QTL were highly correlated with the atherogenic traits. A majority of these candidates have already known atherogenic potential in humans and/or mice, but integrative QTL, eQTL, and correlation analyses further pointed Ptprk as a major candidate of the Chr10 QTL, while Pten and Cyp2c67 of the Chr19 QTL in our DO-F1 cohort. Finally, through additional analyses of RNA-seq data we identified genetic regulation of hepatic transcription factors, including Nr1h3, contributes to atherogenesis in this cohort. Thus, an integrative approach using DO-F1 mice effectively validates the influence of genetic factors on atherosclerosis in DO mice and suggests an opportunity to discover therapeutics in the setting of hyperlipidemia.
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Affiliation(s)
- Myungsuk Kim
- Department of Nutrition, University of California, Davis, CA, USA
- Korea Institute of Science and Technology (KIST), Gangneung, Gangwon-Do, Republic of Korea
- Division of Bio-Medical Science and Technology, KIST School, University of Science and Technology (UST), Seoul, 02792, Republic of Korea
| | - M Nazmul Huda
- Department of Nutrition, University of California, Davis, CA, USA
- Western Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Davis, CA, USA
| | - Levi W Evans
- Western Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Davis, CA, USA
| | - Excel Que
- Western Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Davis, CA, USA
| | - Erik R Gertz
- Western Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Davis, CA, USA
| | - Nobuyo Maeda-Smithies
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Brian J Bennett
- Department of Nutrition, University of California, Davis, CA, USA.
- Western Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Davis, CA, USA.
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16
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Chella Krishnan K, El Hachem EJ, Keller MP, Patel SG, Carroll L, Vegas AD, Gerdes Gyuricza I, Light C, Cao Y, Pan C, Kaczor-Urbanowicz KE, Shravah V, Anum D, Pellegrini M, Lee CF, Seldin MM, Rosenthal NA, Churchill GA, Attie AD, Parker B, James DE, Lusis AJ. Genetic architecture of heart mitochondrial proteome influencing cardiac hypertrophy. eLife 2023; 12:e82619. [PMID: 37276142 PMCID: PMC10241513 DOI: 10.7554/elife.82619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 05/18/2023] [Indexed: 06/07/2023] Open
Abstract
Mitochondria play an important role in both normal heart function and disease etiology. We report analysis of common genetic variations contributing to mitochondrial and heart functions using an integrative proteomics approach in a panel of inbred mouse strains called the Hybrid Mouse Diversity Panel (HMDP). We performed a whole heart proteome study in the HMDP (72 strains, n=2-3 mice) and retrieved 848 mitochondrial proteins (quantified in ≥50 strains). High-resolution association mapping on their relative abundance levels revealed three trans-acting genetic loci on chromosomes (chr) 7, 13 and 17 that regulate distinct classes of mitochondrial proteins as well as cardiac hypertrophy. DAVID enrichment analyses of genes regulated by each of the loci revealed that the chr13 locus was highly enriched for complex-I proteins (24 proteins, P=2.2E-61), the chr17 locus for mitochondrial ribonucleoprotein complex (17 proteins, P=3.1E-25) and the chr7 locus for ubiquinone biosynthesis (3 proteins, P=6.9E-05). Follow-up high resolution regional mapping identified NDUFS4, LRPPRC and COQ7 as the candidate genes for chr13, chr17 and chr7 loci, respectively, and both experimental and statistical analyses supported their causal roles. Furthermore, a large cohort of Diversity Outbred mice was used to corroborate Lrpprc gene as a driver of mitochondrial DNA (mtDNA)-encoded gene regulation, and to show that the chr17 locus is specific to heart. Variations in all three loci were associated with heart mass in at least one of two independent heart stress models, namely, isoproterenol-induced heart failure and diet-induced obesity. These findings suggest that common variations in certain mitochondrial proteins can act in trans to influence tissue-specific mitochondrial functions and contribute to heart hypertrophy, elucidating mechanisms that may underlie genetic susceptibility to heart failure in human populations.
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Affiliation(s)
- Karthickeyan Chella Krishnan
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of MedicineCincinnatiUnited States
| | - Elie-Julien El Hachem
- Department of Integrative Biology and Physiology, Field Systems Biology, Sciences Sorbonne UniversitéParisFrance
| | - Mark P Keller
- Biochemistry Department, University of Wisconsin-MadisonMadisonUnited States
| | - Sanjeet G Patel
- Department of Surgery/Division of Cardiac Surgery, University of Southern California Keck School of MedicineLos AngelesUnited States
| | - Luke Carroll
- Metabolic Systems Biology Laboratory, Charles Perkins Centre, School of Life and Environmental Sciences, University of SydneySydneyAustralia
| | - Alexis Diaz Vegas
- Metabolic Systems Biology Laboratory, Charles Perkins Centre, School of Life and Environmental Sciences, University of SydneySydneyAustralia
| | | | - Christine Light
- Cardiovascular Biology Research Program, Oklahoma Medical Research FoundationOklahoma CityUnited States
| | - Yang Cao
- Department of Medicine/Division of Cardiology, University of California, Los AngelesLos AngelesUnited States
| | - Calvin Pan
- Department of Medicine/Division of Cardiology, University of California, Los AngelesLos AngelesUnited States
| | - Karolina Elżbieta Kaczor-Urbanowicz
- Division of Oral Biology and Medicine, UCLA School of DentistryLos AngelesUnited States
- UCLA Institute for Quantitative and Computational BiosciencesLos AngelesUnited States
| | - Varun Shravah
- Department of Chemistry, University of CaliforniaLos AngelesUnited States
| | - Diana Anum
- Department of Integrative Biology and Physiology, University of CaliforniaLos AngelesUnited States
| | - Matteo Pellegrini
- UCLA Institute for Quantitative and Computational BiosciencesLos AngelesUnited States
| | - Chi Fung Lee
- Cardiovascular Biology Research Program, Oklahoma Medical Research FoundationOklahoma CityUnited States
- Department of Physiology, University of Oklahoma Health Sciences CenterOklahoma CityUnited States
| | - Marcus M Seldin
- Center for Epigenetics and MetabolismIrvineUnited States
- Department of Biological Chemistry, University of CaliforniaIrvineUnited States
| | | | | | - Alan D Attie
- Biochemistry Department, University of Wisconsin-MadisonMadisonUnited States
| | - Benjamin Parker
- Department of Anatomy and Physiology, University of MelbourneMelbourneAustralia
| | - David E James
- Metabolic Systems Biology Laboratory, Charles Perkins Centre, School of Life and Environmental Sciences, University of SydneySydneyAustralia
| | - Aldons J Lusis
- Department of Medicine/Division of Cardiology, University of California, Los AngelesLos AngelesUnited States
- Department of Human Genetics, University of CaliforniaLos AngelesUnited States
- Department of Microbiology, Immunology and Molecular Genetics, University of CaliforniaLos AngelesUnited States
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17
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Moore TM, Lee S, Olsen T, Morselli M, Strumwasser AR, Lin AJ, Zhou Z, Abrishami A, Garcia SM, Bribiesca J, Cory K, Whitney K, Ho T, Ho T, Lee JL, Rucker DH, Nguyen CQA, Anand ATS, Yackly A, Mendoza LQ, Leyva BK, Aliman C, Artiga DJ, Meng Y, Charugundla S, Pan C, Jedian V, Seldin MM, Ahn IS, Diamante G, Blencowe M, Yang X, Mouisel E, Pellegrini M, Turcotte LP, Birkeland KI, Norheim F, Drevon CA, Lusis AJ, Hevener AL. Conserved multi-tissue transcriptomic adaptations to exercise training in humans and mice. Cell Rep 2023; 42:112499. [PMID: 37178122 DOI: 10.1016/j.celrep.2023.112499] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 11/04/2022] [Accepted: 04/26/2023] [Indexed: 05/15/2023] Open
Abstract
Physical activity is associated with beneficial adaptations in human and rodent metabolism. We studied over 50 complex traits before and after exercise intervention in middle-aged men and a panel of 100 diverse strains of female mice. Candidate gene analyses in three brain regions, muscle, liver, heart, and adipose tissue of mice indicate genetic drivers of clinically relevant traits, including volitional exercise volume, muscle metabolism, adiposity, and hepatic lipids. Although ∼33% of genes differentially expressed in skeletal muscle following the exercise intervention are similar in mice and humans independent of BMI, responsiveness of adipose tissue to exercise-stimulated weight loss appears controlled by species and underlying genotype. We leveraged genetic diversity to generate prediction models of metabolic trait responsiveness to volitional activity offering a framework for advancing personalized exercise prescription. The human and mouse data are publicly available via a user-friendly Web-based application to enhance data mining and hypothesis development.
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Affiliation(s)
- Timothy M Moore
- Division of Cardiology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA; Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Sindre Lee
- Department of Transplantation, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Thomas Olsen
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Marco Morselli
- Department of Molecular, Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA, USA; UCLA-DOE Institute for Genomics and Proteomics, University of California Los Angeles, Los Angeles, CA, USA; Institute for Quantitative and Computational Biosciences - The Collaboratory, University of California, Los Angeles, Los Angeles, CA, USA
| | - Alexander R Strumwasser
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Amanda J Lin
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA; Department of Chemical and Systems Biology, Stanford School of Medicine, Stanford, CA, USA
| | - Zhenqi Zhou
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Aaron Abrishami
- Department of Transplantation, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Steven M Garcia
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Jennifer Bribiesca
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Kevin Cory
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Kate Whitney
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Theodore Ho
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Timothy Ho
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Joseph L Lee
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Daniel H Rucker
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Christina Q A Nguyen
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Akshay T S Anand
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Aidan Yackly
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Lorna Q Mendoza
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Brayden K Leyva
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Claudia Aliman
- Department of Transplantation, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Daniel J Artiga
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Yonghong Meng
- Division of Cardiology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Sarada Charugundla
- Division of Cardiology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Calvin Pan
- Division of Cardiology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Vida Jedian
- Division of Cardiology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA
| | - Marcus M Seldin
- Division of Cardiology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine 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
| | - In Sook Ahn
- Molecular, Cellular, and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
| | - Graciel Diamante
- Molecular, Cellular, and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
| | - Montgomery Blencowe
- Molecular, Cellular, and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA; Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, Los Angeles, CA, USA
| | - Xia Yang
- Molecular, Cellular, and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA; Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA; Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, Los Angeles, CA, USA
| | - Etienne Mouisel
- Institute of Metabolic and Cardiovascular Diseases, UMR1297 Inserm, Paul Sabatier University, Toulouse, France
| | - Matteo Pellegrini
- UCLA-DOE Institute for Genomics and Proteomics, University of California Los Angeles, Los Angeles, CA, USA
| | - Lorraine P Turcotte
- Department of Biological Sciences, Dana & David Dornsife College of Letters, Arts, and Sciences, University of Southern California, Los Angeles, CA, USA
| | - Kåre I Birkeland
- Department of Transplantation, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Frode Norheim
- Division of Cardiology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA; Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Christian A Drevon
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Aldons J Lusis
- Division of Cardiology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine 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
| | - Andrea L Hevener
- Division of Endocrinology, Diabetes, and Hypertension, Department of Medicine, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA, USA; Iris Cantor-UCLA Women's Health Research Center, Los Angeles, CA, USA; Veterans Administration Greater Los Angeles Healthcare System, Geriatric Research Education and Clinical Center (GRECC), Los Angeles, CA, USA.
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18
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Oyesola O, Downie AE, Howard N, Barre RS, Kiwanuka K, Zaldana K, Chen YH, Menezes A, Lee SC, Devlin J, Mondragón-Palomino O, Souza COS, Herrmann C, Koralov S, Cadwell K, Graham AL, Loke P. Genetic and Environmental interactions contribute to immune variation in rewilded mice. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.17.533121. [PMID: 36993484 PMCID: PMC10055251 DOI: 10.1101/2023.03.17.533121] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
Abstract
The relative and synergistic contributions of genetics and environment to inter-individual immune response variation remain unclear, despite its implications for understanding both evolutionary biology and medicine. Here, we quantify interactive effects of genotype and environment on immune traits by investigating three inbred mouse strains rewilded in an outdoor enclosure and infected with the parasite, Trichuris muris. Whereas cytokine response heterogeneity was primarily driven by genotype, cellular composition heterogeneity was shaped by interactions between genotype and environment. Notably, genetic differences under laboratory conditions can be decreased following rewilding, and variation in T cell markers are more driven by genetics, whereas B cell markers are driven more by environment. Importantly, variation in worm burden is associated with measures of immune variation, as well as genetics and environment. These results indicate that nonheritable influences interact with genetic factors to shape immune variation, with synergistic impacts on the deployment and evolution of defense mechanisms.
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Affiliation(s)
- Oyebola Oyesola
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institute of Health; Bethesda, MD, USA
| | - Alexander E. Downie
- Department of Ecology and Evolutionary Biology, Princeton University; Princeton, NJ, USA
| | - Nina Howard
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institute of Health; Bethesda, MD, USA
| | - Ramya S. Barre
- Department of Ecology and Evolutionary Biology, Princeton University; Princeton, NJ, USA
| | - Kasalina Kiwanuka
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institute of Health; Bethesda, MD, USA
| | - Kimberly Zaldana
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institute of Health; Bethesda, MD, USA
| | - Ying-Han Chen
- Kimmel Center for Biology and Medicine at the Skirball Institute, New York University, Grossman School of Medicine; New York, NY, USA
| | - Arthur Menezes
- Department of Ecology and Evolutionary Biology, Princeton University; Princeton, NJ, USA
| | - Soo Ching Lee
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institute of Health; Bethesda, MD, USA
| | - Joseph Devlin
- Kimmel Center for Biology and Medicine at the Skirball Institute, New York University, Grossman School of Medicine; New York, NY, USA
| | - Octavio Mondragón-Palomino
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institute of Health; Bethesda, MD, USA
| | - Camila Oliveira Silva Souza
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institute of Health; Bethesda, MD, USA
| | - Christin Herrmann
- Kimmel Center for Biology and Medicine at the Skirball Institute, New York University, Grossman School of Medicine; New York, NY, USA
| | - Sergei Koralov
- Kimmel Center for Biology and Medicine at the Skirball Institute, New York University, Grossman School of Medicine; New York, NY, USA
| | - Ken Cadwell
- Kimmel Center for Biology and Medicine at the Skirball Institute, New York University, Grossman School of Medicine; New York, NY, USA
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Andrea L. Graham
- Department of Ecology and Evolutionary Biology, Princeton University; Princeton, NJ, USA
- Santa Fe Institute, Santa Fe, NM, USA
| | - P’ng Loke
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institute of Health; Bethesda, MD, USA
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19
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Keele GR. Which mouse multiparental population is right for your study? The Collaborative Cross inbred strains, their F1 hybrids, or the Diversity Outbred population. G3 (BETHESDA, MD.) 2023; 13:jkad027. [PMID: 36735601 PMCID: PMC10085760 DOI: 10.1093/g3journal/jkad027] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 12/30/2022] [Accepted: 01/23/2023] [Indexed: 02/04/2023]
Abstract
Multiparental populations (MPPs) encompass greater genetic diversity than traditional experimental crosses of two inbred strains, enabling broader surveys of genetic variation underlying complex traits. Two such mouse MPPs are the Collaborative Cross (CC) inbred panel and the Diversity Outbred (DO) population, which are descended from the same eight inbred strains. Additionally, the F1 intercrosses of CC strains (CC-RIX) have been used and enable study designs with replicate outbred mice. Genetic analyses commonly used by researchers to investigate complex traits in these populations include characterizing how heritable a trait is, i.e. its heritability, and mapping its underlying genetic loci, i.e. its quantitative trait loci (QTLs). Here we evaluate the relative merits of these populations for these tasks through simulation, as well as provide recommendations for performing the quantitative genetic analyses. We find that sample populations that include replicate animals, as possible with the CC and CC-RIX, provide more efficient and precise estimates of heritability. We report QTL mapping power curves for the CC, CC-RIX, and DO across a range of QTL effect sizes and polygenic backgrounds for samples of 174 and 500 mice. The utility of replicate animals in the CC and CC-RIX for mapping QTLs rapidly decreased as traits became more polygenic. Only large sample populations of 500 DO mice were well-powered to detect smaller effect loci (7.5-10%) for highly complex traits (80% polygenic background). All results were generated with our R package musppr, which we developed to simulate data from these MPPs and evaluate genetic analyses from user-provided genotypes.
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Affiliation(s)
- Gregory R Keele
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA
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20
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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: 0] [Impact Index Per Article: 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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21
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Minchew EC, Williamson NC, Readyoff AT, McClung JM, Spangenburg EE. Isometric skeletal muscle contractile properties in common strains of male laboratory mice. Front Physiol 2022; 13:937132. [PMID: 36267576 PMCID: PMC9576934 DOI: 10.3389/fphys.2022.937132] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 09/09/2022] [Indexed: 11/13/2022] Open
Abstract
Assessing contractile function of skeletal muscle in murine models is a commonly employed laboratory technique that investigators utilize to measure the impact of genetic manipulations, drug efficacy, or other therapeutic interventions. Often overlooked is the potential for the strain of the mouse to influence the functional properties of the skeletal muscle. Thus, we sought to characterize commonly assessed isometric force measures in the hindlimb muscles across a variety of mouse strains. Using 6-8-week-old male mice, we measured isometric force, fatigue susceptibility, relaxation kinetics, muscle mass, myofiber cross-sectional area, and fiber type composition of the extensor digitorum longus (EDL) and soleus muscles in C57BL/6NJ, BALB/cJ, FVB/NJ, C57BL/6J, and C57BL/10 mice. The data demonstrate both unique differences and a number of similarities between both muscles in the various genetic backgrounds of mice. Soleus muscle specific force (i.e., force per unit size) exhibited higher variation across strains while specific force of the EDL muscle exhibited minimal variation. In contrast, absolute force differed only in a few mouse strains whereas analysis of muscle morphology revealed many distinctions when compared across all the groups. Collectively, the data suggest that the strain of the mouse can potentially influence the measured biological outcome and may possibly promote a synergistic effect with any genetic manipulation or therapeutic intervention. Thus, it is critical for the investigator to carefully consider the genetic background of the mouse used in the experimental design and precisely document the strain of mouse employed during publication.
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Affiliation(s)
- Everett C. Minchew
- Department of Physiology, East Carolina University Brody School of Medicine, Greenville, NC, United States
| | - Nicholas C. Williamson
- Department of Physiology, East Carolina University Brody School of Medicine, Greenville, NC, United States
| | - Andrew T. Readyoff
- Department of Physiology, East Carolina University Brody School of Medicine, Greenville, NC, United States
| | - Joseph M. McClung
- Department of Physiology, East Carolina University Brody School of Medicine, Greenville, NC, United States,East Carolina University, East Carolina Diabetes and Obesity Institute, Greenville, NC, United States,East Carolina Heart Institute, Greenville, NC, United States
| | - Espen E. Spangenburg
- Department of Physiology, East Carolina University Brody School of Medicine, Greenville, NC, United States,East Carolina University, East Carolina Diabetes and Obesity Institute, Greenville, NC, United States,*Correspondence: Espen E. Spangenburg,
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22
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Cao Y, Wang Y, Zhou Z, Pan C, Jiang L, Zhou Z, Meng Y, Charugundla S, Li T, Allayee H, Seldin MM, Lusis AJ. Liver-heart cross-talk mediated by coagulation factor XI protects against heart failure. Science 2022; 377:1399-1406. [PMID: 36137043 PMCID: PMC9639660 DOI: 10.1126/science.abn0910] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Tissue-tissue communication by endocrine factors is a vital mechanism for physiologic homeostasis. A systems genetics analysis of transcriptomic and functional data from a cohort of diverse, inbred strains of mice predicted that coagulation factor XI (FXI), a liver-derived protein, protects against diastolic dysfunction, a key trait of heart failure with preserved ejection fraction. This was confirmed using gain- and loss-of-function studies, and FXI was found to activate the bone morphogenetic protein (BMP)-SMAD1/5 pathway in the heart. The proteolytic activity of FXI is required for the cleavage and activation of extracellular matrix-associated BMP7 in the heart, thus inhibiting genes involved in inflammation and fibrosis. Our results reveal a protective role of FXI in heart injury that is distinct from its role in coagulation.
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Affiliation(s)
- Yang Cao
- Department of Medicine, Division of Cardiology, University of California, Los Angeles, CA 90095, USA
| | - Yuchen Wang
- Department of Medicine, Division of Cardiology, University of California, Los Angeles, CA 90095, USA
| | - Zhenqi Zhou
- Division of Endocrinology, Diabetes and Hypertension, Department of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Calvin Pan
- Department of Medicine, Division of Cardiology, University of California, Los Angeles, CA 90095, USA
| | - Ling Jiang
- Department of Anesthesiology, Laboratory of Mitochondria and Metabolism, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Zhiqiang Zhou
- Department of Medicine, Division of Cardiology, University of California, Los Angeles, CA 90095, USA
| | - Yonghong Meng
- Department of Medicine, Division of Cardiology, University of California, Los Angeles, CA 90095, USA
| | - Sarada Charugundla
- Department of Medicine, Division of Cardiology, University of California, Los Angeles, CA 90095, USA
| | - Tao Li
- Department of Anesthesiology, Laboratory of Mitochondria and Metabolism, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Hooman Allayee
- Departments of Population and Public Health Sciences and Biochemistry and Molecular Medicine, University of Southern California Keck School of Medicine, Los Angeles, CA 90089, USA
| | - Marcus M. Seldin
- Department of Biological Chemistry and Center for Epigenetics and Metabolism, University of California, Irvine School of Medicine, Irvine, CA 92697, USA
| | - Aldons J. Lusis
- Department of Medicine, Division of Cardiology, University of California, Los Angeles, CA 90095, USA.,Department of Human Genetics, University of California, Los Angeles, CA 90095, USA.,Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, CA 90095, USA.,Corresponding author.
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23
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Pattee J, Vanderlinden LA, Mahaffey S, Hoffman P, Tabakoff B, Saba LM. Evaluation and characterization of expression quantitative trait analysis methods in the Hybrid Rat Diversity Panel. Front Genet 2022; 13:947423. [PMID: 36186443 PMCID: PMC9515987 DOI: 10.3389/fgene.2022.947423] [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: 05/18/2022] [Accepted: 08/26/2022] [Indexed: 01/07/2023] Open
Abstract
The Hybrid Rat Diversity Panel (HRDP) is a stable and well-characterized set of more than 90 inbred rat strains that can be leveraged for systems genetics approaches to understanding the genetic and genomic variation associated with complex disease. The HRDP exhibits substantial between-strain diversity while retaining substantial within-strain isogenicity, allowing for the precise mapping of genetic variation associated with complex phenotypes and providing statistical power to identify associated variants. In order to robustly identify associated genetic variants, it is important to account for the population structure induced by inbreeding. To this end, we investigate the performance of four plausible approaches towards modeling quantitative traits in the HRDP and quantify their operating characteristics. In particular, we investigate three approaches based on genome-wide mixed model analysis, and one approach based on ordinary least squares linear regression. Towards facilitating study planning and design, we conduct extensive simulations to investigate the power of genetic association analyses in the HRDP, and characterize the impressive attained power. In simulation of eQTL data in the HRDP, we find that a mixed model approach that leverages leave-one-chromosome-out kinship estimation attains the highest power while controlling type I error.
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Affiliation(s)
- Jack Pattee
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Lauren A. Vanderlinden
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Spencer Mahaffey
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Paula Hoffman
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, United States,Department of Pharmacology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Boris Tabakoff
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Laura M. Saba
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, United States,*Correspondence: Laura M. Saba,
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Bauer S, Eigenmann J, Zhao Y, Fleig J, Hawe JS, Pan C, Bongiovanni D, Wengert S, Ma A, Lusis AJ, Kovacic JC, Björkegren JLM, Maegdefessel L, Schunkert H, von Scheidt M. Identification of the Transcription Factor ATF3 as a Direct and Indirect Regulator of the LDLR. Metabolites 2022; 12:metabo12090840. [PMID: 36144244 PMCID: PMC9504235 DOI: 10.3390/metabo12090840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 08/28/2022] [Accepted: 09/02/2022] [Indexed: 11/16/2022] Open
Abstract
Coronary artery disease (CAD) is a complex, multifactorial disease caused, in particular, by inflammation and cholesterol metabolism. At the molecular level, the role of tissue-specific signaling pathways leading to CAD is still largely unexplored. This study relied on two main resources: (1) genes with impact on atherosclerosis/CAD, and (2) liver-specific transcriptome analyses from human and mouse studies. The transcription factor activating transcription factor 3 (ATF3) was identified as a key regulator of a liver network relevant to atherosclerosis and linked to inflammation and cholesterol metabolism. ATF3 was predicted to be a direct and indirect (via MAF BZIP Transcription Factor F (MAFF)) regulator of low-density lipoprotein receptor (LDLR). Chromatin immunoprecipitation DNA sequencing (ChIP-seq) data from human liver cells revealed an ATF3 binding motif in the promoter regions of MAFF and LDLR. siRNA knockdown of ATF3 in human Hep3B liver cells significantly upregulated LDLR expression (p < 0.01). Inflammation induced by lipopolysaccharide (LPS) stimulation resulted in significant upregulation of ATF3 (p < 0.01) and subsequent downregulation of LDLR (p < 0.001). Liver-specific expression data from human CAD patients undergoing coronary artery bypass grafting (CABG) surgery (STARNET) and mouse models (HMDP) confirmed the regulatory role of ATF3 in the homeostasis of cholesterol metabolism. This study suggests that ATF3 might be a promising treatment candidate for lowering LDL cholesterol and reducing cardiovascular risk.
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Affiliation(s)
- Sabine Bauer
- Department of Cardiology, German Heart Centre Munich, Technical University Munich, 80636 Munich, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany
- Correspondence: (S.B.); (M.v.S.); Tel.: +49-(0)89-1218-2367 (S.B.); +49-(0)89-1218-2849 (M.v.S.)
| | - Jana Eigenmann
- Department of Cardiology, German Heart Centre Munich, Technical University Munich, 80636 Munich, Germany
| | - Yuqi Zhao
- Department of Integrative Biology and Physiology, Institute for Quantitative and Computational Biosciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Julia Fleig
- Department of Cardiology, German Heart Centre Munich, Technical University Munich, 80636 Munich, Germany
| | - Johann S. Hawe
- Department of Cardiology, German Heart Centre Munich, Technical University Munich, 80636 Munich, Germany
| | - Calvin Pan
- Departments of Medicine, Human Genetics, Microbiology, Immunology and Molecular Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Dario Bongiovanni
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany
- Division of Cardiology, Cardiocentro Ticino Institute, Ente Ospedaliero Cantonale, 6900 Lugano, Switzerland
| | - Simon Wengert
- Helmholtz Pioneer Campus, Helmholtz Center Munich, 85764 Neuherberg, Germany
- Institute of Computational Biology, Helmholtz Center Munich, 85764 Oberschleißheim, Germany
| | - Angela Ma
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Aldons J. Lusis
- Departments of Medicine, Human Genetics, Microbiology, Immunology and Molecular Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Jason C. Kovacic
- Victor Chang Cardiac Research Institute, Darlinghurst, Sydney, NSW 2010, Australia
- St. Vincent’s Clinical School, University of New South Wales, Darlinghurst, Sydney, NSW 2010, Australia
- Icahn School of Medicine at Mount Sinai, Cardiovascular Research Institute, New York, NY 10029, USA
| | - Johan L. M. Björkegren
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Clinical Gene Networks AB, 114 44 Stockholm, Sweden
- Integrated Cardio Metabolic Centre, Karolinska Institutet, Novum, Huddinge, 171 77 Stockholm, Sweden
| | - Lars Maegdefessel
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany
- Department of Vascular and Endovascular Surgery, Klinikum Rechts der Isar, Technical University Munich, 81675 Munich, Germany
- Department of Molecular Medicine and Surgery, Karolinska Institutet, 171 76 Stockholm, Sweden
| | - Heribert Schunkert
- Department of Cardiology, German Heart Centre Munich, Technical University Munich, 80636 Munich, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany
| | - Moritz von Scheidt
- Department of Cardiology, German Heart Centre Munich, Technical University Munich, 80636 Munich, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, 80802 Munich, Germany
- Correspondence: (S.B.); (M.v.S.); Tel.: +49-(0)89-1218-2367 (S.B.); +49-(0)89-1218-2849 (M.v.S.)
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25
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Ramirez MA, Ninoyu Y, Miller C, Andrade LR, Edassery S, Bomba-Warczak E, Ortega B, Manor U, Rutherford MA, Friedman RA, Savas JN. Cochlear ribbon synapse maturation requires Nlgn1 and Nlgn3. iScience 2022; 25:104803. [PMID: 35992071 PMCID: PMC9386149 DOI: 10.1016/j.isci.2022.104803] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 05/10/2022] [Accepted: 07/15/2022] [Indexed: 01/13/2023] Open
Abstract
Hearing depends on precise synaptic transmission between cochlear inner hair cells and spiral ganglion neurons through afferent ribbon synapses. Neuroligins (Nlgns) facilitate synapse maturation in the brain, but they have gone unstudied in the cochlea. We report Nlgn3 and Nlgn1 knockout (KO) cochleae have fewer ribbon synapses and have impaired hearing. Nlgn3 KO is more vulnerable to noise trauma with limited activity at high frequencies one day after noise. Furthermore, Nlgn3 KO cochleae have a 5-fold reduction in synapse number compared to wild type after two weeks of recovery. Double KO cochlear phenotypes are more prominent than the KOs, for example, 5-fold smaller synapses, 25% reduction in synapse density, and 30% less synaptic output. These observations indicate Nlgn3 and Nlgn1 are essential to cochlear ribbon synapse maturation and function.
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Affiliation(s)
- Miguel A. Ramirez
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Yuzuru Ninoyu
- Division of Otolaryngology, Department of Surgery, University of California, San Diego, 9500 Gilman Drive, Mail Code 0666, La Jolla, CA 92093, USA
| | - Cayla Miller
- Waitt Advanced Biophotonics Core, Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, CA 92037, USA
| | - Leonardo R. Andrade
- Waitt Advanced Biophotonics Core, Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, CA 92037, USA
| | - Seby Edassery
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Ewa Bomba-Warczak
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Briana Ortega
- Division of Otolaryngology, Department of Surgery, University of California, San Diego, 9500 Gilman Drive, Mail Code 0666, La Jolla, CA 92093, USA
| | - Uri Manor
- Waitt Advanced Biophotonics Core, Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, CA 92037, USA
| | - Mark A. Rutherford
- Department of Otolaryngology, Washington University in St. Louis School of Medicine, St. Louis, MO, USA
| | - Rick A. Friedman
- Division of Otolaryngology, Department of Surgery, University of California, San Diego, 9500 Gilman Drive, Mail Code 0666, La Jolla, CA 92093, USA
| | - Jeffrey N. Savas
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
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26
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Ilyas I, Little PJ, Liu Z, Xu Y, Kamato D, Berk BC, Weng J, Xu S. Mouse models of atherosclerosis in translational research. Trends Pharmacol Sci 2022; 43:920-939. [PMID: 35902281 DOI: 10.1016/j.tips.2022.06.009] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 06/12/2022] [Accepted: 06/17/2022] [Indexed: 12/21/2022]
Abstract
Atherosclerotic cardiovascular disease (CVD), the major cause of premature human mortality, is a chronic and progressive metabolic and inflammatory disease in large- and medium-sized arteries. Mouse models are widely used to gain mechanistic insights into the pathogenesis of atherosclerosis and have facilitated the discovery of anti-atherosclerotic drugs. Despite promising preclinical studies, many drug candidates have not translated to clinical use because of the complexity of disease patho-mechanisms including lipid metabolic traits and inflammatory, genetic, and hemodynamic factors. We review the current preclinical utility and translation potential of traditional [apolipoprotein E (APOE)- and low-density lipoprotein (LDL) receptor (LDLR)-deficient mice] and emerging mouse models that include partial carotid ligation and AAV8-Pcsk9-D377Y injection in atherosclerosis research and drug discovery. This article represents an important resource in atherosclerosis research.
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Affiliation(s)
- Iqra Ilyas
- Department of Endocrinology, Institute of Endocrine and Metabolic Diseases, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Clinical Research Hospital of Chinese Academy of Sciences (Hefei), University of Science and Technology of China, Hefei, China
| | - Peter J Little
- School of Pharmacy, University of Queensland, Pharmacy Australia Centre of Excellence, Woolloongabba, QLD, Australia
| | - Zhiping Liu
- Guangdong Province Key Laboratory of Pharmacodynamic Constituents of Traditional Chinese Medicine and New Drugs Research, College of Pharmacy, Jinan University, Guangzhou, China
| | - Yanyong Xu
- Key Laboratory of Metabolism and Molecular Medicine of the Ministry of Education, Department of Pathology of School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Danielle Kamato
- School of Pharmacy, University of Queensland, Pharmacy Australia Centre of Excellence, Woolloongabba, QLD, Australia; Griffith Institute for Drug Discovery, School of Environment and Science, Griffith University, Brisbane, Australia
| | - Bradford C Berk
- Aab Cardiovascular Research Institute, Department of Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA
| | - Jianping Weng
- Department of Endocrinology, Institute of Endocrine and Metabolic Diseases, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Clinical Research Hospital of Chinese Academy of Sciences (Hefei), University of Science and Technology of China, Hefei, China; Laboratory of Metabolics and Cardiovascular Diseases, Institute of Endocrine and Metabolic Diseases, University of Science and Technology of China, Hefei, China; Biomedical Sciences and Health Laboratory of Anhui Province, University of Science and Technology of China, Hefei, China.
| | - Suowen Xu
- Department of Endocrinology, Institute of Endocrine and Metabolic Diseases, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Clinical Research Hospital of Chinese Academy of Sciences (Hefei), University of Science and Technology of China, Hefei, China; Laboratory of Metabolics and Cardiovascular Diseases, Institute of Endocrine and Metabolic Diseases, University of Science and Technology of China, Hefei, China; Biomedical Sciences and Health Laboratory of Anhui Province, University of Science and Technology of China, Hefei, China.
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Olguín V, Durán A, Las Heras M, Rubilar JC, Cubillos FA, Olguín P, Klein AD. Genetic Background Matters: Population-Based Studies in Model Organisms for Translational Research. Int J Mol Sci 2022; 23:ijms23147570. [PMID: 35886916 PMCID: PMC9316598 DOI: 10.3390/ijms23147570] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 06/28/2022] [Accepted: 07/04/2022] [Indexed: 02/01/2023] Open
Abstract
We are all similar but a bit different. These differences are partially due to variations in our genomes and are related to the heterogeneity of symptoms and responses to treatments that patients exhibit. Most animal studies are performed in one single strain with one manipulation. However, due to the lack of variability, therapies are not always reproducible when treatments are translated to humans. Panels of already sequenced organisms are valuable tools for mimicking human phenotypic heterogeneities and gene mapping. This review summarizes the current knowledge of mouse, fly, and yeast panels with insightful applications for translational research.
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Affiliation(s)
- Valeria Olguín
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana Universidad del Desarrollo, Santiago 7610658, Chile; (V.O.); (A.D.); (M.L.H.); (J.C.R.)
| | - Anyelo Durán
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana Universidad del Desarrollo, Santiago 7610658, Chile; (V.O.); (A.D.); (M.L.H.); (J.C.R.)
| | - Macarena Las Heras
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana Universidad del Desarrollo, Santiago 7610658, Chile; (V.O.); (A.D.); (M.L.H.); (J.C.R.)
| | - Juan Carlos Rubilar
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana Universidad del Desarrollo, Santiago 7610658, Chile; (V.O.); (A.D.); (M.L.H.); (J.C.R.)
| | - Francisco A. Cubillos
- Departamento de Biología, Santiago, Facultad de Química y Biología, Universidad de Santiago de Chile, Santiago 9170022, Chile;
- Millennium Institute for Integrative Biology (iBio), Santiago 7500565, Chile
| | - Patricio Olguín
- Program in Human Genetics, Institute of Biomedical Sciences, Biomedical Neurosciences Institute, Department of Neuroscience, Facultad de Medicina, Universidad de Chile, Santiago 8380453, Chile;
| | - Andrés D. Klein
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana Universidad del Desarrollo, Santiago 7610658, Chile; (V.O.); (A.D.); (M.L.H.); (J.C.R.)
- Correspondence:
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28
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Oraha J, Enriquez RF, Herzog H, Lee NJ. Sex-specific changes in metabolism during the transition from chow to high-fat diet feeding are abolished in response to dieting in C57BL/6J mice. Int J Obes (Lond) 2022; 46:1749-1758. [PMID: 35794191 PMCID: PMC9492540 DOI: 10.1038/s41366-022-01174-4] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 06/13/2022] [Accepted: 06/14/2022] [Indexed: 12/03/2022]
Abstract
Background/Objective Female mice are often excluded from diet-induced obesity studies as they are more resistant to the obesifying effects of a high-fat diet (HFD). However, the underlying mechanisms behind this sex disparity may actually have important implications for the development and management of obesity in humans. Therefore, we systematically investigated the immediate sex-specific effects of transitioning to a HFD in C57BL/6J mice as well as monitored whether these effects are altered after sustained HFD feeding and whether sex affects the response to a return to chow, representative of dieting. Methods Dual X-ray absorptiometry (DXA) analysis of body composition, indirect calorimetry measurements, and qPCR analysis of hypothalamic and brainstem regions were performed on male and female C57BL/6J mice. Results HFD had immediate and dramatic effects in males, increasing fat mass by 58% in the first 3 days. The resistance to the obesifying effect of HFD in females was linked both to an ability to maintain activity levels as well as to an immediate and significantly enhanced reduction in respiratory quotient (RQ), suggesting a greater ability to utilise fat in the diet as a source of fuel. Mechanistically, this sex disparity may be at least partially due to inherent sex differences in the catabolic (POMC/CART) versus anabolic (NPY/AgRP) neurological signalling pathways. Interestingly, the reintroduction of chow following HFD had immediate and consistent responses between the sexes with body composition and most metabolic parameters normalised within 3 days. However, both sexes displayed elevated hypothalamic Npy levels reminiscent of starvation. The difference in RQ seen between the sexes on HFD was immediately abolished suggesting similar abilities to burn fat reserves for fuel. Conclusions C57BL/6J mice have markedly different sex-specific behavioural and metabolic responses to the introduction as well as the sustained intake of a HFD, but consistent responses to a dieting situation.
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Affiliation(s)
- Jennifer Oraha
- Garvan Institute of Medical Research, Sydney, NSW, Australia
| | | | - Herbert Herzog
- Garvan Institute of Medical Research, Sydney, NSW, Australia. .,School of Clinical Medicine, UNSW Sydney, Sydney, NSW, Australia.
| | - Nicola J Lee
- Garvan Institute of Medical Research, Sydney, NSW, Australia. .,School of Clinical Medicine, UNSW Sydney, Sydney, NSW, Australia.
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29
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Cao Y, Vergnes L, Wang YC, Pan C, Chella Krishnan K, Moore TM, Rosa-Garrido M, Kimball TH, Zhou Z, Charugundla S, Rau CD, Seldin MM, Wang J, Wang Y, Vondriska TM, Reue K, Lusis AJ. Sex differences in heart mitochondria regulate diastolic dysfunction. Nat Commun 2022; 13:3850. [PMID: 35787630 PMCID: PMC9253085 DOI: 10.1038/s41467-022-31544-5] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 06/15/2022] [Indexed: 01/10/2023] Open
Abstract
Heart failure with preserved ejection fraction (HFpEF) exhibits a sex bias, being more common in women than men, and we hypothesize that mitochondrial sex differences might underlie this bias. As part of genetic studies of heart failure in mice, we observe that heart mitochondrial DNA levels and function tend to be reduced in females as compared to males. We also observe that expression of genes encoding mitochondrial proteins are higher in males than females in human cohorts. We test our hypothesis in a panel of genetically diverse inbred strains of mice, termed the Hybrid Mouse Diversity Panel (HMDP). Indeed, we find that mitochondrial gene expression is highly correlated with diastolic function, a key trait in HFpEF. Consistent with this, studies of a "two-hit" mouse model of HFpEF confirm that mitochondrial function differs between sexes and is strongly associated with a number of HFpEF traits. By integrating data from human heart failure and the mouse HMDP cohort, we identify the mitochondrial gene Acsl6 as a genetic determinant of diastolic function. We validate its role in HFpEF using adenoviral over-expression in the heart. We conclude that sex differences in mitochondrial function underlie, in part, the sex bias in diastolic function.
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Affiliation(s)
- Yang Cao
- Division of Cardiology, Department of Medicine, University of California, Los Angeles, CA, USA
| | - Laurent Vergnes
- Metabolism Theme, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90024, USA
| | - Yu-Chen Wang
- Division of Cardiology, Department of Medicine, University of California, Los Angeles, CA, USA
| | - Calvin Pan
- Division of Cardiology, Department of Medicine, University of California, Los Angeles, CA, USA
| | - Karthickeyan Chella Krishnan
- Division of Cardiology, Department of Medicine, University of California, Los Angeles, CA, USA
- Department of Pharmacology and Physiology, University of Cincinnati College of Medicine, Cincinnati, USA
| | - Timothy M Moore
- Division of Cardiology, Department of Medicine, University of California, Los Angeles, CA, USA
| | - Manuel Rosa-Garrido
- Department of Biomedical Engineering, School of Medicine and School of Engineering, University of Alabama at Birmingham, Birmingham, AL, 35233, USA
| | - Todd H Kimball
- Department of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Zhiqiang Zhou
- Division of Cardiology, Department of Medicine, University of California, Los Angeles, CA, USA
| | - Sarada Charugundla
- Division of Cardiology, Department of Medicine, University of California, Los Angeles, CA, USA
| | - Christoph D Rau
- Department of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Marcus M Seldin
- Division of Cardiology, Department of Medicine, University of California, Los Angeles, CA, USA
| | - Jessica Wang
- Division of Cardiology, Department of Medicine, University of California, Los Angeles, CA, USA
| | - Yibin Wang
- Department of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Department of Physiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Thomas M Vondriska
- Department of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Department of Physiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Karen Reue
- Metabolism Theme, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90024, USA
- Molecular Biology Institute at UCLA, Los Angeles, CA, 90095, USA
| | - Aldons J Lusis
- Division of Cardiology, Department of Medicine, University of California, Los Angeles, CA, USA.
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90024, USA.
- Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, CA, USA.
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30
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Abstract
Sex is a key risk factor for many types of cardiovascular disease. It is imperative to understand the mechanisms underlying sex differences to devise optimal preventive and therapeutic approaches for all individuals. Both biological sex (determined by sex chromosomes and gonadal hormones) and gender (social and cultural behaviors associated with femininity or masculinity) influence differences between men and women in disease susceptibility and pathology. Here, we focus on the application of experimental mouse models that elucidate the influence of 2 components of biological sex-sex chromosome complement (XX or XY) and gonad type (ovaries or testes). These models have revealed that in addition to well-known effects of gonadal hormones, sex chromosome complement influences cardiovascular risk factors, such as plasma cholesterol levels and adiposity, as well as the development of atherosclerosis and pulmonary hypertension. One mechanism by which sex chromosome dosage influences cardiometabolic traits is through sex-biased expression of X chromosome genes that escape X inactivation. These include chromatin-modifying enzymes that regulate gene expression throughout the genome. The identification of factors that determine sex-biased gene expression and cardiometabolic traits will expand our mechanistic understanding of cardiovascular disease processes and provide insight into sex differences that remain throughout the lifespan as gonadal hormone levels alter with age.
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Affiliation(s)
- Karen Reue
- Department of Human Genetics, David Geffen School of Medicine at UCLA
- Department of Medicine, David Geffen School of Medicine at UCLA
- Molecular Biology Institute, University of California, Los Angeles, CA 90095
| | - Carrie B. Wiese
- Department of Human Genetics, David Geffen School of Medicine at UCLA
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31
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Boussaty EC, Friedman RA, Clifford RE. Hearing loss and tinnitus: association studies for complex-hearing disorders in mouse and man. Hum Genet 2022; 141:981-990. [PMID: 34318347 PMCID: PMC8792513 DOI: 10.1007/s00439-021-02317-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 07/13/2021] [Indexed: 12/29/2022]
Abstract
Genome-wide association studies (GWAS) provide an unbiased first look at genetic loci involved in aging and noise-induced sensorineural hearing loss and tinnitus. The hearing phenotype, whether audiogram-based or self-report, is regressed against genotyped information at representative single nucleotide polymorphisms (SNPs) across the genome. Findings include the fact that both hearing loss and tinnitus are polygenic disorders, with up to thousands of genes, each of effect size of < 0.02. Smaller human GWAS' were able to use objective measures and identified a few loci; however, hundreds of thousands of participants have been required for the statistical power to identify significant variants, and GWAS is unable to assess rare variants with mean allele frequency < 1%. Animal studies are required as well because of inability to access the human cochlea. Mouse GWAS builds on linkage techniques and the known phenotypic differences in auditory function between inbred strains. With the advantage that the laboratory environment can be controlled for noise and aging, the Hybrid Mouse Diversity Panel (HDMP) combines 100 strains sequenced at high resolution. Lift-over regions between mice and humans have identified over 17,000 homologous genes. Since most significant SNPs are either intergenic or in introns, and binding sites between species are poorly preserved between species, expression quantitative trait locus information is required to bring humans and mice into agreement. Transcriptome-wide analysis studies (TWAS) can prioritize putative causal genes and tissues. Diverse species, each making a distinct contribution, carry a synergistic advantage in the quest for treatment and ultimate cure of sensorineural hearing difficulties.
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Affiliation(s)
- Ely Cheikh Boussaty
- School of Health Sciences, Division of Otolaryngology, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Rick Adam Friedman
- School of Health Sciences, Division of Otolaryngology, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Royce E Clifford
- School of Health Sciences, Division of Otolaryngology, University of California San Diego, La Jolla, San Diego, CA, USA.
- Research Department, VA Hospitals San Diego, San Diego, CA, USA.
- Visiting Scientist, Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA.
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Bjørklund MM, Bernal JA, Bentzon JF. Atherosclerosis Induced by Adeno-Associated Virus Encoding Gain-of-Function PCSK9. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2022; 2419:461-473. [PMID: 35237981 DOI: 10.1007/978-1-0716-1924-7_27] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Induction of atherosclerosis in mice with one or more genetic alterations (e.g., conditional deletion of a gene of interest) has traditionally required crossbreeding with Apoe or Ldlr deficient mice to achieve sufficient hypercholesterolemia. However, this procedure is time consuming and generates a surplus of mice with genotypes that are irrelevant for experiments. Several alternative methods exist that obviate the need to work in mice with germline-encoded hypercholesterolemia. In this chapter, we detail an efficient and increasingly used method to induce hypercholesterolemia in mice through adeno-associated virus-mediated transfer of the proprotein convertase subtilisin/kexin type 9 (PCSK9) gene.
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Affiliation(s)
- Martin Mæng Bjørklund
- Department of Clinical Medicine, Heart Diseases, Aarhus University, Aarhus, Denmark
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
| | - Juan A Bernal
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
| | - Jacob F Bentzon
- Department of Clinical Medicine, Heart Diseases, Aarhus University, Aarhus, Denmark.
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.
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Fields PD, McTaggart S, Reisser CMO, Haag C, Palmer WH, Little TJ, Ebert D, Obbard DJ. Population-genomic analysis identifies a low rate of global adaptive fixation in the proteins of the cyclical parthenogen Daphnia magna. Mol Biol Evol 2022; 39:6542319. [PMID: 35244177 PMCID: PMC8963301 DOI: 10.1093/molbev/msac048] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Daphnia are well-established ecological and evolutionary models, and the interaction between D. magna and its microparasites is widely considered a paragon of the host-parasite coevolutionary process. Like other well-studied arthropods such as Drosophila melanogaster and Anopheles gambiae, D. magna is a small, widespread, and abundant species that is therefore expected to display a large long-term population size and high rates of adaptive protein evolution. However, unlike these other species, D. magna is cyclically asexual and lives in a highly structured environment (ponds and lakes) with moderate levels of dispersal, both of which are predicted to impact upon long-term effective population size and adaptive protein evolution. To investigate patterns of adaptive protein fixation, we produced the complete coding genomes of 36 D. magna clones sampled from across the European range (Western Palaearctic), along with draft sequences for the close relatives D. similis and D. lumholtzi, used as outgroups. We analyzed genome-wide patterns of adaptive fixation, with a particular focus on genes that have an a priori expectation of high rates, such as those likely to mediate immune responses, RNA interference against viruses and transposable elements, and those with a strongly male-biased expression pattern. We find that, as expected, D. magna displays high levels of diversity and that this is highly structured among populations. However, compared with Drosophila, we find that D. magna proteins appear to have a high proportion of weakly deleterious variants and do not show evidence of pervasive adaptive fixation across its entire range. This is true of the genome as a whole, and also of putative ‘arms race’ genes that often show elevated levels of adaptive substitution in other species. In addition to the likely impact of extensive, and previously documented, local adaptation, we speculate that these findings may reflect reduced efficacy of selection associated with cyclical asexual reproduction.
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Affiliation(s)
- Peter D Fields
- University of Basel, Department of Environmental Sciences, Zoology, Vesalgasse 1, Basel, CH-4051, Switzerland
| | - Seanna McTaggart
- Institute of Evolutionary Biology; School of Biological Sciences University of Edinburgh, Edinburgh, EH9 3JT, United Kingdom
| | - Céline M O Reisser
- Centre d'Ecologie Fonctionnelle et Evolutive CEFE UMR 5175, Univ Montpellier, CNRS, EPHE, IRD, Univ Paul Valéry Montpellier 3, campus CNRS, 1919, route de Mende, 34293 Montpellier Cedex 5, France.,MARBEC, Univ Montpellier, CNRS, IFREMER, IRD, Montpellier, France
| | - Christoph Haag
- Centre d'Ecologie Fonctionnelle et Evolutive CEFE UMR 5175, Univ Montpellier, CNRS, EPHE, IRD, Univ Paul Valéry Montpellier 3, campus CNRS, 1919, route de Mende, 34293 Montpellier Cedex 5, France
| | - William H Palmer
- Institute of Evolutionary Biology; School of Biological Sciences University of Edinburgh, Edinburgh, EH9 3JT, United Kingdom
| | - Tom J Little
- Institute of Evolutionary Biology; School of Biological Sciences University of Edinburgh, Edinburgh, EH9 3JT, United Kingdom
| | - Dieter Ebert
- University of Basel, Department of Environmental Sciences, Zoology, Vesalgasse 1, Basel, CH-4051, Switzerland
| | - Darren J Obbard
- Institute of Evolutionary Biology; School of Biological Sciences University of Edinburgh, Edinburgh, EH9 3JT, United Kingdom
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Bhattacharya A, Freedman AN, Avula V, Harris R, Liu W, Pan C, Lusis AJ, Joseph RM, Smeester L, Hartwell HJ, Kuban KCK, Marsit CJ, Li Y, O’Shea TM, Fry RC, Santos HP. Placental genomics mediates genetic associations with complex health traits and disease. Nat Commun 2022; 13:706. [PMID: 35121757 PMCID: PMC8817049 DOI: 10.1038/s41467-022-28365-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 12/15/2021] [Indexed: 01/09/2023] Open
Abstract
AbstractAs the master regulator in utero, the placenta is core to the Developmental Origins of Health and Disease (DOHaD) hypothesis but is historically understudied. To identify placental gene-trait associations (GTAs) across the life course, we perform distal mediator-enriched transcriptome-wide association studies (TWAS) for 40 traits, integrating placental multi-omics from the Extremely Low Gestational Age Newborn Study. At $$P \; < \; 2.5\times {10}^{-6}$$
P
<
2.5
×
10
−
6
, we detect 248 GTAs, mostly for neonatal and metabolic traits, across 176 genes, enriched for cell growth and immunological pathways. In aggregate, genetic effects mediated by placental expression significantly explain 4 early-life traits but no later-in-life traits. 89 GTAs show significant mediation through distal genetic variants, identifying hypotheses for distal regulation of GTAs. Investigation of one hypothesis in human placenta-derived choriocarcinoma cells reveal that knockdown of mediator gene EPS15 upregulates predicted targets SPATA13 and FAM214A, both associated with waist-hip ratio in TWAS, and multiple genes involved in metabolic pathways. These results suggest profound health impacts of placental genomic regulation in developmental programming across the life course.
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35
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Bartolomé A. Stem Cell-Derived β Cells: A Versatile Research Platform to Interrogate the Genetic Basis of β Cell Dysfunction. Int J Mol Sci 2022; 23:501. [PMID: 35008927 PMCID: PMC8745644 DOI: 10.3390/ijms23010501] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 12/27/2021] [Accepted: 12/29/2021] [Indexed: 02/07/2023] Open
Abstract
Pancreatic β cell dysfunction is a central component of diabetes progression. During the last decades, the genetic basis of several monogenic forms of diabetes has been recognized. Genome-wide association studies (GWAS) have also facilitated the identification of common genetic variants associated with an increased risk of diabetes. These studies highlight the importance of impaired β cell function in all forms of diabetes. However, how most of these risk variants confer disease risk, remains unanswered. Understanding the specific contribution of genetic variants and the precise role of their molecular effectors is the next step toward developing treatments that target β cell dysfunction in the era of personalized medicine. Protocols that allow derivation of β cells from pluripotent stem cells, represent a powerful research tool that allows modeling of human development and versatile experimental designs that can be used to shed some light on diabetes pathophysiology. This article reviews different models to study the genetic basis of β cell dysfunction, focusing on the recent advances made possible by stem cell applications in the field of diabetes research.
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Affiliation(s)
- Alberto Bartolomé
- Instituto de Investigaciones Biomédicas Alberto Sols, CSIC-UAM, 28029 Madrid, Spain
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36
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Koplev S, Seldin M, Sukhavasi K, Ermel R, Pang S, Zeng L, Bankier S, Di Narzo A, Cheng H, Meda V, Ma A, Talukdar H, Cohain A, Amadori L, Argmann C, Houten SM, Franzén O, Mocci G, Meelu OA, Ishikawa K, Whatling C, Jain A, Jain RK, Gan LM, Giannarelli C, Roussos P, Hao K, Schunkert H, Michoel T, Ruusalepp A, Schadt EE, Kovacic JC, Lusis AJ, Björkegren JLM. A mechanistic framework for cardiometabolic and coronary artery diseases. NATURE CARDIOVASCULAR RESEARCH 2022; 1:85-100. [PMID: 36276926 PMCID: PMC9583458 DOI: 10.1038/s44161-021-00009-1] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/19/2023]
Abstract
Coronary atherosclerosis results from the delicate interplay of genetic and exogenous risk factors, principally taking place in metabolic organs and the arterial wall. Here we show that 224 gene-regulatory coexpression networks (GRNs) identified by integrating genetic and clinical data from patients with (n = 600) and without (n = 250) coronary artery disease (CAD) with RNA-seq data from seven disease-relevant tissues in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study largely capture this delicate interplay, explaining >54% of CAD heritability. Within 89 cross-tissue GRNs associated with clinical severity of CAD, 374 endocrine factors facilitated inter-organ interactions, primarily along an axis from adipose tissue to the liver (n = 152). This axis was independently replicated in genetically diverse mouse strains and by injection of recombinant forms of adipose endocrine factors (EPDR1, FCN2, FSTL3 and LBP) that markedly altered blood lipid and glucose levels in mice. Altogether, the STARNET database and the associated GRN browser (http://starnet.mssm.edu) provide a multiorgan framework for exploration of the molecular interplay between cardiometabolic disorders and CAD.
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Affiliation(s)
- Simon Koplev
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marcus Seldin
- Departments of Medicine, Human Genetics and Microbiology, Immunology & 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, CA, USA
| | - Katyayani Sukhavasi
- Department of Cardiac Surgery and the Heart Clinic, Tartu University Hospital and Department of Cardiology, Institute of Clinical Medicine, Tartu University, Tartu, Estonia
| | - Raili Ermel
- Department of Cardiac Surgery and the Heart Clinic, Tartu University Hospital and Department of Cardiology, Institute of Clinical Medicine, Tartu University, Tartu, Estonia
| | - Shichao Pang
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, DZHK (German Centre for Cardiovascular Research), Munich Heart Alliance, Munich, Germany
| | - Lingyao Zeng
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, DZHK (German Centre for Cardiovascular Research), Munich Heart Alliance, Munich, Germany
| | - Sean Bankier
- BHF Centre for Cardiovascular Science, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, UK
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | - Antonio Di Narzo
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Haoxiang Cheng
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Vamsidhar Meda
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Angela Ma
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Husain Talukdar
- Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Ariella Cohain
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Letizia Amadori
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- New York University Cardiovascular Research Center, Department of Medicine, Leon H. Charney Division of Cardiology, New York University Grossman School of Medicine, New York University Langone Health, New York, NY, USA
| | - Carmen Argmann
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sander M. Houten
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Oscar Franzén
- Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Giuseppe Mocci
- Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
| | - Omar A. Meelu
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kiyotake Ishikawa
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Carl Whatling
- Translational Science and Experimental Medicine, Research and Early Development, Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Anamika Jain
- Department of Cardiac Surgery and the Heart Clinic, Tartu University Hospital and Department of Cardiology, Institute of Clinical Medicine, Tartu University, Tartu, Estonia
| | - Rajeev Kumar Jain
- Department of Cardiac Surgery and the Heart Clinic, Tartu University Hospital and Department of Cardiology, Institute of Clinical Medicine, Tartu University, Tartu, Estonia
| | - Li-Ming Gan
- Early Clinical Development, Research and Early Development, Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Chiara Giannarelli
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- New York University Cardiovascular Research Center, Department of Medicine, Leon H. Charney Division of Cardiology, New York University Grossman School of Medicine, New York University Langone Health, New York, NY, USA
| | - Panos Roussos
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY, USA
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Sema4, Stamford, CT, USA
| | - Heribert Schunkert
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, DZHK (German Centre for Cardiovascular Research), Munich Heart Alliance, Munich, Germany
| | - Tom Michoel
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | - Arno Ruusalepp
- Department of Cardiac Surgery and the Heart Clinic, Tartu University Hospital and Department of Cardiology, Institute of Clinical Medicine, Tartu University, Tartu, Estonia
- Clinical Gene Networks AB, Stockholm, Sweden
| | - Eric E. Schadt
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Sema4, Stamford, CT, USA
| | - Jason C. Kovacic
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Victor Chang Cardiac Research Institute, Darlinghurst, New South Wales, Australia
- St Vincent’s Clinical School, University of NSW, Sydney, New South Wales, Australia
| | - Aldon J. Lusis
- Departments of Medicine, Human Genetics and Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Johan L. M. Björkegren
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden
- Clinical Gene Networks AB, Stockholm, Sweden
- Correspondence and requests for materials should be addressed to Johan L. M. Björkegren.
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37
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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; 11:82951. [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] [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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38
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Li L, Chen Z, von Scheidt M, Li S, Steiner A, Güldener U, Koplev S, Ma A, Hao K, Pan C, Lusis AJ, Pang S, Kessler T, Ermel R, Sukhavasi K, Ruusalepp A, Gagneur J, Erdmann J, Kovacic JC, Björkegren JLM, Schunkert H. Transcriptome-wide association study of coronary artery disease identifies novel susceptibility genes. Basic Res Cardiol 2022; 117:6. [PMID: 35175464 PMCID: PMC8852935 DOI: 10.1007/s00395-022-00917-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 01/18/2022] [Accepted: 02/01/2022] [Indexed: 01/31/2023]
Abstract
The majority of risk loci identified by genome-wide association studies (GWAS) are in non-coding regions, hampering their functional interpretation. Instead, transcriptome-wide association studies (TWAS) identify gene-trait associations, which can be used to prioritize candidate genes in disease-relevant tissue(s). Here, we aimed to systematically identify susceptibility genes for coronary artery disease (CAD) by TWAS. We trained prediction models of nine CAD-relevant tissues using EpiXcan based on two genetics-of-gene-expression panels, the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) and the Genotype-Tissue Expression (GTEx). Based on these prediction models, we imputed gene expression of respective tissues from individual-level genotype data on 37,997 CAD cases and 42,854 controls for the subsequent gene-trait association analysis. Transcriptome-wide significant association (i.e. P < 3.85e-6) was observed for 114 genes. Of these, 96 resided within previously identified GWAS risk loci and 18 were novel. Stepwise analyses were performed to study their plausibility, biological function, and pathogenicity in CAD, including analyses for colocalization, damaging mutations, pathway enrichment, phenome-wide associations with human data and expression-traits correlations using mouse data. Finally, CRISPR/Cas9-based gene knockdown of two newly identified TWAS genes, RGS19 and KPTN, in a human hepatocyte cell line resulted in reduced secretion of APOB100 and lipids in the cell culture medium. Our CAD TWAS work (i) prioritized candidate causal genes at known GWAS loci, (ii) identified 18 novel genes to be associated with CAD, and iii) suggested potential tissues and pathways of action for these TWAS CAD genes.
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Affiliation(s)
- Ling Li
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Fakultät für Informatik, Technische Universität München, Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Zhifen Chen
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Moritz von Scheidt
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Shuangyue Li
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Andrea Steiner
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Ulrich Güldener
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Simon Koplev
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574 USA
| | - Angela Ma
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574 USA
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574 USA
| | - Calvin Pan
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA USA
| | - Aldons J. Lusis
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA USA ,Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA USA ,Department of Microbiology, Immunology and Molecular Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA USA
| | - Shichao Pang
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Thorsten Kessler
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany ,Department of Microbiology, Immunology and Molecular Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA USA
| | - Raili Ermel
- Department of Cardiac Surgery, The Heart Clinic, Tartu University Hospital, Tartu, Estonia
| | - Katyayani Sukhavasi
- Department of Cardiac Surgery, The Heart Clinic, Tartu University Hospital, Tartu, Estonia
| | - Arno Ruusalepp
- Department of Cardiac Surgery, The Heart Clinic, Tartu University Hospital, Tartu, Estonia ,Clinical Gene Networks AB, Stockholm, Sweden
| | - Julien Gagneur
- Fakultät für Informatik, Technische Universität München, Munich, Germany
| | - Jeanette Erdmann
- DZHK (German Research Centre for Cardiovascular Research), Partner Site Hamburg/Lübeck/Kiel, Lübeck, Germany ,Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Jason C. Kovacic
- Victor Chang Cardiac Research Institute, Darlinghurst, Australia ,St Vincent’s Clinical School, University of New South Wales, Sydney, Australia ,Icahn School of Medicine at Mount Sinai, Cardiovascular Research Institute, New York, NY 10029-6574 USA
| | - Johan L. M. Björkegren
- Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029-6574 USA ,Clinical Gene Networks AB, Stockholm, Sweden ,Department of Medicine, Huddinge, Karolinska Institutet, Karolinska Universitetssjukhuset, Stockholm, Sweden
| | - Heribert Schunkert
- Department of Cardiology, German Heart Center Munich, Technical University Munich, Lazarettstraße 36, 80636 Munich, Germany ,Deutsches Zentrum für Herz- und Kreislaufforschung (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
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Clark KC, Kwitek AE. Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome. Compr Physiol 2021; 12:3045-3084. [PMID: 34964118 PMCID: PMC9373910 DOI: 10.1002/cphy.c210010] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.
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Affiliation(s)
- Karen C Clark
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Anne E Kwitek
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
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40
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Winkels H, Ghosheh Y, Kobiyama K, Kiosses WB, Orecchioni M, Ehinger E, Suryawanshi V, Herrera-De La Mata S, Marchovecchio P, Riffelmacher T, Thiault N, Kronenberg M, Wolf D, Seumois G, Vijayanand P, Ley K. Thymus-Derived CD4 +CD8 + Cells Reside in Mediastinal Adipose Tissue and the Aortic Arch. THE JOURNAL OF IMMUNOLOGY 2021; 207:2720-2732. [PMID: 34740961 DOI: 10.4049/jimmunol.2100208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 09/04/2021] [Indexed: 11/19/2022]
Abstract
Double-positive CD4+CD8αβ+ (DP) cells are thought to reside as T cell progenitors exclusively within the thymus. We recently discovered an unexpected CD4+ and CD8αβ+ immune cell population in healthy and atherosclerotic mice by single-cell RNA sequencing. Transcriptomically, these cells resembled thymic DPs. Flow cytometry and three-dimensional whole-mount imaging confirmed DPs in thymus, mediastinal adipose tissue, and aortic adventitia, but nowhere else. Deep transcriptional profiling revealed differences between DP cells isolated from the three locations. All DPs were dependent on RAG2 expression and the presence of the thymus. Mediastinal adipose tissue DPs resided in close vicinity to invariant NKT cells, which they could activate in vitro. Thymus transplantation failed to reconstitute extrathymic DPs, and frequencies of extrathymic DPs were unaltered by pharmacologic inhibition of S1P1, suggesting that their migration may be locally confined. Our results define two new, transcriptionally distinct subsets of extrathymic DPs that may play a role in aortic vascular homeostasis.
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Affiliation(s)
- Holger Winkels
- La Jolla Institute for Immunology, La Jolla, CA; .,Department of Cardiology, Clinic III for Internal Medicine, University of Cologne, Cologne, Germany
| | | | | | | | | | | | | | | | | | | | | | | | - Dennis Wolf
- University Hospital Freiburg, Freiburg, Germany; and
| | | | | | - Klaus Ley
- La Jolla Institute for Immunology, La Jolla, CA.,Department of Bioengineering, University of California, San Diego, La Jolla, CA
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41
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Zhang QJ, He Y, Li Y, Shen H, Lin L, Zhu M, Wang Z, Luo X, Hill JA, Cao D, Luo RL, Zou R, McAnally J, Liao J, Bajona P, Zang QS, Yu Y, Liu ZP. Matricellular Protein Cilp1 Promotes Myocardial Fibrosis in Response to Myocardial Infarction. Circ Res 2021; 129:1021-1035. [PMID: 34610755 DOI: 10.1161/circresaha.121.319482] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- Qing-Jun Zhang
- Internal Medicine-Cardiology Division (Q.-J.Z., M.Z., X.L., J.A.H., D.C., R.L.L., R.Z., Z.-P.L.), UT Southwestern Medical Center, Dallas, TX
| | - Yu He
- Department of Clinical Laboratory, First Affiliated hospital of Guangxi Medical University, China (Y.H.)
| | - Yongnan Li
- The Sixth General Surgery, Biliary & Vascular surgery, Shengjing Hospital of China Medical University, China (Y.L.)
| | - Huali Shen
- Institutes of Biochemical Science, Fudan University, China (H.S., L.L.)
| | - Ling Lin
- Institutes of Biochemical Science, Fudan University, China (H.S., L.L.)
| | - Min Zhu
- Internal Medicine-Cardiology Division (Q.-J.Z., M.Z., X.L., J.A.H., D.C., R.L.L., R.Z., Z.-P.L.), UT Southwestern Medical Center, Dallas, TX
| | - Zhaoning Wang
- Department of Molecular Biology (Z.W., J.A.H., J.M., Z.-P.L.), UT Southwestern Medical Center, Dallas, TX
| | - Xiang Luo
- Internal Medicine-Cardiology Division (Q.-J.Z., M.Z., X.L., J.A.H., D.C., R.L.L., R.Z., Z.-P.L.), UT Southwestern Medical Center, Dallas, TX
| | - Joseph A Hill
- Internal Medicine-Cardiology Division (Q.-J.Z., M.Z., X.L., J.A.H., D.C., R.L.L., R.Z., Z.-P.L.), UT Southwestern Medical Center, Dallas, TX.,Department of Molecular Biology (Z.W., J.A.H., J.M., Z.-P.L.), UT Southwestern Medical Center, Dallas, TX
| | - Dian Cao
- Internal Medicine-Cardiology Division (Q.-J.Z., M.Z., X.L., J.A.H., D.C., R.L.L., R.Z., Z.-P.L.), UT Southwestern Medical Center, Dallas, TX
| | - Richard L Luo
- Internal Medicine-Cardiology Division (Q.-J.Z., M.Z., X.L., J.A.H., D.C., R.L.L., R.Z., Z.-P.L.), UT Southwestern Medical Center, Dallas, TX
| | - Raymond Zou
- Internal Medicine-Cardiology Division (Q.-J.Z., M.Z., X.L., J.A.H., D.C., R.L.L., R.Z., Z.-P.L.), UT Southwestern Medical Center, Dallas, TX
| | - John McAnally
- Department of Molecular Biology (Z.W., J.A.H., J.M., Z.-P.L.), UT Southwestern Medical Center, Dallas, TX
| | - Jun Liao
- Department of Bioengineering, University of Texas at Arlington (J.L.)
| | - Pietro Bajona
- Department of Cardiovascular and Thoracic Surgery (P.B.), UT Southwestern Medical Center, Dallas, TX.,Allegheny Health Network-Drexel University College of Medicine, Pittsburgh, PA (P.B.)
| | - Qun S Zang
- Department of Surgery, Stritch School of Medicine, Burn & Shock Trauma Research Institute, Loyola University, Maywood, IL (Q.S.Z.)
| | - Yonghao Yu
- Department of Biochemistry (Y.Y.), UT Southwestern Medical Center, Dallas, TX
| | - Zhi-Ping Liu
- Internal Medicine-Cardiology Division (Q.-J.Z., M.Z., X.L., J.A.H., D.C., R.L.L., R.Z., Z.-P.L.), UT Southwestern Medical Center, Dallas, TX.,Department of Molecular Biology (Z.W., J.A.H., J.M., Z.-P.L.), UT Southwestern Medical Center, Dallas, TX
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42
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Zheng A, Li H, Feng Z, Liu J. Integrative Analyses Reveal Tstd1 as a Potential Modulator of HDL Cholesterol and Mitochondrial Function in Mice. Cells 2021; 10:2976. [PMID: 34831199 PMCID: PMC8616306 DOI: 10.3390/cells10112976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 10/25/2021] [Accepted: 10/27/2021] [Indexed: 11/16/2022] Open
Abstract
High-density lipoprotein (HDL) cholesterol levels are closely associated with human health and diseases. To identify genes modulating plasma HDL levels, we integrated HDL measurements and multi-omics data collected from diverse mouse cohorts and combined a list of systems genetics methods, including quantitative trait loci (QTL) mapping analysis, mediation analysis, transcriptome-wide association analysis (TWAS), and correlation analysis. We confirmed a significant and conserved QTL for plasma HDL on chromosome 1 and identified that Tstd1 liver transcript correlates with plasma HDL in several independent mouse cohorts, suggesting Tstd1 may be a potential modulator of plasma HDL levels. Correlation analysis using over 70 transcriptomics datasets in humans and mice revealed consistent correlations between Tstd1 and genes known to be involved in cholesterol and HDL regulation. Consistent with strong enrichment in gene sets related to cholesterol and lipoproteins in the liver, mouse strains with high Tstd1 exhibited higher plasma levels of HDL, total cholesterol and other lipid markers. GeneBridge using large-scale expression datasets identified conserved and positive associations between TSTD1/Tstd1 and mitochondrial pathways, as well as cholesterol and lipid pathways in human, mouse and rat. In summary, we identified Tstd1 as a new modulator of plasma HDL and mitochondrial function through integrative systems analyses, and proposed a new mechanism of HDL modulation and a potential therapeutic target for relevant diseases. This study highlights the value of such integrative approaches in revealing molecular mechanisms of complex traits or diseases.
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Affiliation(s)
- Adi Zheng
- Department of Biomedical Sciences, University of Lausanne, Bugnon 7, 1005 Lausanne, Switzerland;
| | - Hao Li
- Center for Mitochondrial Biology and Medicine, The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, China;
| | - Zhihui Feng
- Center for Mitochondrial Biology and Medicine, The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, China;
| | - Jiankang Liu
- Center for Mitochondrial Biology and Medicine, The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, China;
- University of Health and Rehabilitation Sciences, Qingdao 266071, China
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43
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Xu H, Thomas MJ, Kaul S, Kallinger R, Ouweneel AB, Maruko E, Oussaada SM, Jongejan A, Cense HA, Nieuwdorp M, Serlie MJ, Goldberg IJ, Civelek M, Parks BW, Lusis AJ, Knaack D, Schill RL, May SC, Reho JJ, Grobe JL, Gantner B, Sahoo D, Sorci-Thomas MG. Pcpe2, a Novel Extracellular Matrix Protein, Regulates Adipocyte SR-BI-Mediated High-Density Lipoprotein Uptake. Arterioscler Thromb Vasc Biol 2021; 41:2708-2725. [PMID: 34551590 PMCID: PMC8551036 DOI: 10.1161/atvbaha.121.316615] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Accepted: 08/24/2021] [Indexed: 01/22/2023]
Abstract
Objective To investigate the role of adipocyte Pcpe2 (procollagen C-endopeptidase enhancer 2) in SR-BI (scavenger receptor class BI)-mediated HDL-C (high-density lipoprotein cholesterol) uptake and contributions to adipose lipid storage. Approach and Results Pcpe2, a glycoprotein devoid of intrinsic proteolytic activity, is believed to participate in extracellular protein-protein interactions, supporting SR-BI- mediated HDL-C uptake. In published studies, Pcpe2 deficiency increased the development of atherosclerosis by reducing SR-BI-mediated HDL-C catabolism, but the biological impact of this deficiency on adipocyte SR-BI-mediated HDL-C uptake is unknown. Differentiated cells from Ldlr-/-/Pcpe2-/- (Pcpe2-/-) mouse adipose tissue showed elevated SR-BI protein levels, but significantly reduced HDL-C uptake compared to Ldlr-/- (control) adipose tissue. SR-BI-mediated HDL-C uptake was restored by preincubation of cells with exogenous Pcpe2. In diet-fed mice lacking Pcpe2, significant reductions in visceral, subcutaneous, and brown adipose tissue mass were observed, despite elevations in plasma triglyceride and cholesterol concentrations. Significant positive correlations exist between adipose mass and Pcpe2 expression in both mice and humans. Conclusions Overall, these findings reveal a novel and unexpected function for Pcpe2 in modulating SR-BI expression and function as it relates to adipose tissue expansion and cholesterol balance in both mice and humans.
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Affiliation(s)
- Hao Xu
- Department of Medicine, Division of Endocrinology and Molecular Medicine
| | - Michael J. Thomas
- Pharmacology & Toxicology and
- Cardiovascular Center, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Sushma Kaul
- Department of Medicine, Division of Endocrinology and Molecular Medicine
| | | | - Amber B. Ouweneel
- Department of Medicine, Division of Endocrinology and Molecular Medicine
| | - Elisa Maruko
- Department of Medicine, Division of Endocrinology and Molecular Medicine
| | - Sabrina M. Oussaada
- Department of Endocrinology and Metabolism, Amsterdam University Medical Centers, Academic Medical Center, Amsterdam, the Netherlands
| | - Aldo Jongejan
- Department of Bioinformatics, Amsterdam University Medical Centers, Academic Medical Center, Amsterdam, the Netherlands
| | - Huib A. Cense
- Department of Surgery, Rode Kruis Ziekenhuis, Beverwijk, the Netherlands
| | - Max Nieuwdorp
- Department of Internal and Vascular Medicine, Amsterdam University Medical Centers, Academic Medical Center, Amsterdam, the Netherlands
| | - Mireille J. Serlie
- Department of Endocrinology and Metabolism, Amsterdam University Medical Centers, Academic Medical Center, Amsterdam, the Netherlands
| | - Ira J. Goldberg
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, New York University Langone School of Medicine, New York, NY
| | - Mete Civelek
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA
| | - Brian W. Parks
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI
| | - Aldons J. Lusis
- Department of Medicine, Human Genetics, Microbiology, Immunology and Molecular Genetics, University of California Los Angeles, California
| | - Darcy Knaack
- Department of Biochemistry, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Rebecca L. Schill
- Department of Biochemistry, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Sarah C. May
- Department of Biochemistry, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - John J. Reho
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin
- Comprehensive Rodent Metabolic Phenotyping Core
| | - Justin L. Grobe
- Cardiovascular Center, Medical College of Wisconsin, Milwaukee, Wisconsin
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin
- Comprehensive Rodent Metabolic Phenotyping Core
- Department of Biomedical Engineering
| | - Benjamin Gantner
- Department of Medicine, Division of Endocrinology and Molecular Medicine
| | - Daisy Sahoo
- Department of Medicine, Division of Endocrinology and Molecular Medicine
- Pharmacology & Toxicology and
- Cardiovascular Center, Medical College of Wisconsin, Milwaukee, Wisconsin
- Department of Biochemistry, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Mary G. Sorci-Thomas
- Department of Medicine, Division of Endocrinology and Molecular Medicine
- Pharmacology & Toxicology and
- Cardiovascular Center, Medical College of Wisconsin, Milwaukee, Wisconsin
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44
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Abstract
PURPOSE OF REVIEW We provide an overview of recent findings with respect to gene-environment (GxE) interactions for cardiovascular disease (CVD) risk and discuss future opportunities for advancing the field. RECENT FINDINGS Over the last several years, GxE interactions for CVD have mostly been identified for smoking and coronary artery disease (CAD) or related risk factors. By comparison, there is more limited evidence for GxE interactions between CVD outcomes and other exposures, such as physical activity, air pollution, diet, and sex. The establishment of large consortia and population-based cohorts, in combination with new computational tools and mouse genetics platforms, can potentially overcome some of the limitations that have hindered human GxE interaction studies and reveal additional association signals for CVD-related traits. The identification of novel GxE interactions is likely to provide a better understanding of the pathogenesis and genetic liability of CVD, with significant implications for healthy lifestyles and therapeutic strategies.
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45
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Greco CM, Koronowski KB, Smith JG, Shi J, Kunderfranco P, Carriero R, Chen S, Samad M, Welz PS, Zinna VM, Mortimer T, Chun SK, Shimaji K, Sato T, Petrus P, Kumar A, Vaca-Dempere M, Deryagian O, Van C, Kuhn JMM, Lutter D, Seldin MM, Masri S, Li W, Baldi P, Dyar KA, Muñoz-Cánoves P, Benitah SA, Sassone-Corsi P. Integration of feeding behavior by the liver circadian clock reveals network dependency of metabolic rhythms. SCIENCE ADVANCES 2021; 7:eabi7828. [PMID: 34550736 PMCID: PMC8457671 DOI: 10.1126/sciadv.abi7828] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 07/29/2021] [Indexed: 05/28/2023]
Abstract
The mammalian circadian clock, expressed throughout the brain and body, controls daily metabolic homeostasis. Clock function in peripheral tissues is required, but not sufficient, for this task. Because of the lack of specialized animal models, it is unclear how tissue clocks interact with extrinsic signals to drive molecular oscillations. Here, we isolated the interaction between feeding and the liver clock by reconstituting Bmal1 exclusively in hepatocytes (Liver-RE), in otherwise clock-less mice, and controlling timing of food intake. We found that the cooperative action of BMAL1 and the transcription factor CEBPB regulates daily liver metabolic transcriptional programs. Functionally, the liver clock and feeding rhythm are sufficient to drive temporal carbohydrate homeostasis. By contrast, liver rhythms tied to redox and lipid metabolism required communication with the skeletal muscle clock, demonstrating peripheral clock cross-talk. Our results highlight how the inner workings of the clock system rely on communicating signals to maintain daily metabolism.
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Affiliation(s)
- Carolina M. Greco
- Center for Epigenetics and Metabolism, U1233 INSERM, Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA
| | - Kevin B. Koronowski
- Center for Epigenetics and Metabolism, U1233 INSERM, Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA
| | - Jacob G. Smith
- Center for Epigenetics and Metabolism, U1233 INSERM, Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA
| | - Jiejun Shi
- Center for Epigenetics and Metabolism, U1233 INSERM, Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA
| | - Paolo Kunderfranco
- Bioinformatics Unit, Humanitas Clinical and Research Center–IRCCS, Rozzano 20089, Italy
| | - Roberta Carriero
- Bioinformatics Unit, Humanitas Clinical and Research Center–IRCCS, Rozzano 20089, Italy
| | - Siwei Chen
- Institute for Genomics and Bioinformatics, Department of Computer Science, UCI, Irvine, CA 92697, USA
| | - Muntaha Samad
- Institute for Genomics and Bioinformatics, Department of Computer Science, UCI, Irvine, CA 92697, USA
| | - Patrick-Simon Welz
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Barcelona 08028, Spain
- Program in Cancer Research, Hospital del Mar Medical Research Institute (IMIM), Dr. Aiguader 88, Barcelona 08003, Spain
| | - Valentina M. Zinna
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Barcelona 08028, Spain
| | - Thomas Mortimer
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Barcelona 08028, Spain
| | - Sung Kook Chun
- Center for Epigenetics and Metabolism, U1233 INSERM, Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA
| | - Kohei Shimaji
- Center for Epigenetics and Metabolism, U1233 INSERM, Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA
| | - Tomoki Sato
- Center for Epigenetics and Metabolism, U1233 INSERM, Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA
| | - Paul Petrus
- Center for Epigenetics and Metabolism, U1233 INSERM, Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA
| | - Arun Kumar
- Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), CIBER on Neurodegenerative Diseases (CIBERNED), Barcelona 08003, Spain
| | - Mireia Vaca-Dempere
- Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), CIBER on Neurodegenerative Diseases (CIBERNED), Barcelona 08003, Spain
| | - Oleg Deryagian
- Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), CIBER on Neurodegenerative Diseases (CIBERNED), Barcelona 08003, Spain
| | - Cassandra Van
- Center for Epigenetics and Metabolism, U1233 INSERM, Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA
| | - José Manuel Monroy Kuhn
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Computational Discovery Research, Institute for Diabetes and Obesity (IDO), Helmholtz Diabetes Center (HDC), Helmholtz Zentrum München, Neuherberg, Germany
| | - Dominik Lutter
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Computational Discovery Research, Institute for Diabetes and Obesity (IDO), Helmholtz Diabetes Center (HDC), Helmholtz Zentrum München, Neuherberg, Germany
| | - Marcus M. Seldin
- Center for Epigenetics and Metabolism, U1233 INSERM, Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA
| | - Selma Masri
- Center for Epigenetics and Metabolism, U1233 INSERM, Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA
| | - Wei Li
- Center for Epigenetics and Metabolism, U1233 INSERM, Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA
| | - Pierre Baldi
- Institute for Genomics and Bioinformatics, Department of Computer Science, UCI, Irvine, CA 92697, USA
| | - Kenneth A. Dyar
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Metabolic Physiology, Institute for Diabetes and Cancer (IDC), Helmholtz Diabetes Center, Helmholtz Zentrum München, Neuherberg, Germany
| | - Pura Muñoz-Cánoves
- Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), CIBER on Neurodegenerative Diseases (CIBERNED), Barcelona 08003, Spain
- Spanish National Center on Cardiovascular Research (CNIC), Madrid 28029, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona 08010, Spain
| | - Salvador Aznar Benitah
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Barcelona 08028, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona 08010, Spain
| | - Paolo Sassone-Corsi
- Center for Epigenetics and Metabolism, U1233 INSERM, Department of Biological Chemistry, University of California, Irvine, Irvine, CA 92697, USA
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46
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Cao Y, Tang L, Du K, Paraiso K, Sun Q, Liu Z, Ye X, Fang Y, Yuan F, Chen H, Chen Y, Wang X, Yu C, Blitz IL, Wang PH, Huang L, Cheng H, Lu X, Cho KW, Seldin M, Fang Z, Yang Q. Anterograde regulation of mitochondrial genes and FGF21 signaling by hepatic LSD1. JCI Insight 2021; 6:e147692. [PMID: 34314389 PMCID: PMC8492328 DOI: 10.1172/jci.insight.147692] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 07/21/2021] [Indexed: 01/14/2023] Open
Abstract
Mitochondrial biogenesis and function are controlled by anterograde regulatory pathways involving more than 1000 nuclear-encoded proteins. Transcriptional networks controlling the nuclear-encoded mitochondrial genes remain to be fully elucidated. Here, we show that histone demethylase LSD1 KO from adult mouse liver (LSD1-LKO) reduces the expression of one-third of all nuclear-encoded mitochondrial genes and decreases mitochondrial biogenesis and function. LSD1-modulated histone methylation epigenetically regulates nuclear-encoded mitochondrial genes. Furthermore, LSD1 regulates gene expression and protein methylation of nicotinamide mononucleotide adenylyltransferase 1 (NMNAT1), which controls the final step of NAD+ synthesis and limits NAD+ availability in the nucleus. Lsd1 KO reduces NAD+-dependent SIRT1 and SIRT7 deacetylase activity, leading to hyperacetylation and hypofunctioning of GABPβ and PGC-1α, the major transcriptional factor/cofactor for nuclear-encoded mitochondrial genes. Despite the reduced mitochondrial function in the liver, LSD1-LKO mice are protected from diet-induced hepatic steatosis and glucose intolerance, partially due to induction of hepatokine FGF21. Thus, LSD1 orchestrates a core regulatory network involving epigenetic modifications and NAD+ synthesis to control mitochondrial function and hepatokine production.
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Affiliation(s)
- Yang Cao
- Department of Medicine, Physiology and Biophysics, UC Irvine Diabetes Center, University of California Irvine (UCI), Irvine, California, USA
| | - Lingyi Tang
- Department of Medicine, Physiology and Biophysics, UC Irvine Diabetes Center, University of California Irvine (UCI), Irvine, California, USA.,Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Kang Du
- Department of Medicine, Physiology and Biophysics, UC Irvine Diabetes Center, University of California Irvine (UCI), Irvine, California, USA
| | - Kitt Paraiso
- Department of Developmental & Cell Biology, UCI, Irvine, California, USA
| | - Qiushi Sun
- Department of Medicine, Physiology and Biophysics, UC Irvine Diabetes Center, University of California Irvine (UCI), Irvine, California, USA.,Department of Geriatrics, Sir Run Run Hospital of Nanjing Medical University, Nanjing, China
| | - Zhengxia Liu
- Department of Medicine, Physiology and Biophysics, UC Irvine Diabetes Center, University of California Irvine (UCI), Irvine, California, USA
| | - Xiaolong Ye
- Department of Medicine, Physiology and Biophysics, UC Irvine Diabetes Center, University of California Irvine (UCI), Irvine, California, USA
| | - Yuan Fang
- Department of Medicine, Physiology and Biophysics, UC Irvine Diabetes Center, University of California Irvine (UCI), Irvine, California, USA
| | - Fang Yuan
- Department of Medicine, Physiology and Biophysics, UC Irvine Diabetes Center, University of California Irvine (UCI), Irvine, California, USA
| | - Hank Chen
- Department of Medicine, Physiology and Biophysics, UC Irvine Diabetes Center, University of California Irvine (UCI), Irvine, California, USA
| | - Yumay Chen
- Department of Medicine, Physiology and Biophysics, UC Irvine Diabetes Center, University of California Irvine (UCI), Irvine, California, USA
| | - Xiaorong Wang
- Department of Medicine, Physiology and Biophysics, UC Irvine Diabetes Center, University of California Irvine (UCI), Irvine, California, USA
| | - Clinton Yu
- Department of Medicine, Physiology and Biophysics, UC Irvine Diabetes Center, University of California Irvine (UCI), Irvine, California, USA
| | - Ira L. Blitz
- Department of Developmental & Cell Biology, UCI, Irvine, California, USA
| | - Ping H. Wang
- Department of Medicine, Physiology and Biophysics, UC Irvine Diabetes Center, University of California Irvine (UCI), Irvine, California, USA
| | - Lan Huang
- Department of Medicine, Physiology and Biophysics, UC Irvine Diabetes Center, University of California Irvine (UCI), Irvine, California, USA
| | - Haibo Cheng
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Xiang Lu
- Department of Geriatrics, Sir Run Run Hospital of Nanjing Medical University, Nanjing, China
| | - Ken W.Y. Cho
- Department of Developmental & Cell Biology, UCI, Irvine, California, USA
| | - Marcus Seldin
- Department of Biological Chemistry, UCI, Irvine, California, USA
| | - Zhuyuan Fang
- Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Qin Yang
- Department of Medicine, Physiology and Biophysics, UC Irvine Diabetes Center, University of California Irvine (UCI), Irvine, California, USA
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47
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Durán A, Rebolledo-Jaramillo B, Olguin V, Rojas-Herrera M, Las Heras M, Calderón JF, Zanlungo S, Priestman DA, Platt FM, Klein AD. Identification of genetic modifiers of murine hepatic β-glucocerebrosidase activity. Biochem Biophys Rep 2021; 28:101105. [PMID: 34458595 PMCID: PMC8379285 DOI: 10.1016/j.bbrep.2021.101105] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 08/11/2021] [Accepted: 08/12/2021] [Indexed: 12/18/2022] Open
Abstract
The acid β-glucocerebrosidase (GCase) enzyme cleaves glucosylceramide into glucose and ceramide. Loss of function variants in the gene encoding for GCase can lead to Gaucher disease and Parkinson's disease. Therapeutic strategies aimed at increasing GCase activity by targeting a modulating factor are attractive and poorly explored. To identify genetic modifiers, we measured hepatic GCase activity in 27 inbred mouse strains. A genome-wide association study (GWAS) using GCase activity as a trait identified several candidate modifier genes, including Dmrtc2 and Arhgef1 (p=2.1x10−7), and Grik5 (p=2.1x10−7). Bayesian integration of the gene mapping with transcriptomics was used to build integrative networks. The analysis uncovered additional candidate GCase regulators, highlighting modules of the acute phase response (p=1.01x10−8), acute inflammatory response (p=1.01x10−8), fatty acid beta-oxidation (p=7.43x10−5), among others. Our study revealed previously unknown candidate modulators of GCase activity, which may facilitate the design of therapies for diseases with GCase dysfunction. Hepatic GCase activity significantly differs among mouse strains. Genome-wide association study revealed putative modifier genes of GCase activity. Bayesian integration of multi-omics identified a regulatory network of GCase activity. This study may facilitate the design of therapies for diseases with GCase dysfunction.
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Affiliation(s)
- Anyelo Durán
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana, Universidad del Desarrollo, Santiago, Chile
| | - Boris Rebolledo-Jaramillo
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana, Universidad del Desarrollo, Santiago, Chile
| | - Valeria Olguin
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana, Universidad del Desarrollo, Santiago, Chile
| | - Marcelo Rojas-Herrera
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana, Universidad del Desarrollo, Santiago, Chile
| | - Macarena Las Heras
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana, Universidad del Desarrollo, Santiago, Chile
| | - Juan F Calderón
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana, Universidad del Desarrollo, Santiago, Chile
| | - Silvana Zanlungo
- Department of Gastroenterology, Faculty of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - David A Priestman
- Department of Pharmacology, University of Oxford, Oxford, OX1 3QT, UK
| | - Frances M Platt
- Department of Pharmacology, University of Oxford, Oxford, OX1 3QT, UK
| | - Andrés D Klein
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana, Universidad del Desarrollo, Santiago, Chile
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48
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Gordon-Larsen P, French JE, Moustaid-Moussa N, Voruganti VS, Mayer-Davis EJ, Bizon CA, Cheng Z, Stewart DA, Easterbrook JW, Shaikh SR. Synergizing Mouse and Human Studies to Understand the Heterogeneity of Obesity. Adv Nutr 2021; 12:2023-2034. [PMID: 33885739 PMCID: PMC8483969 DOI: 10.1093/advances/nmab040] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 02/17/2021] [Accepted: 03/13/2021] [Indexed: 12/12/2022] Open
Abstract
Obesity is routinely considered as a single disease state, which drives a "one-size-fits-all" approach to treatment. We recently convened the first annual University of North Carolina Interdisciplinary Nutrition Sciences Symposium to discuss the heterogeneity of obesity and the need for translational science to advance understanding of this heterogeneity. The symposium aimed to advance scientific rigor in translational studies from animal to human models with the goal of identifying underlying mechanisms and treatments. In this review, we discuss fundamental gaps in knowledge of the heterogeneity of obesity ranging from cellular to population perspectives. We also advocate approaches to overcoming limitations in the field. Examples include the use of contemporary mouse genetic reference population models such as the Collaborative Cross and Diversity Outbred mice that effectively model human genetic diversity and the use of translational models that integrate -omics and computational approaches from pre-clinical to clinical models of obesity. Finally, we suggest best scientific practices to ensure strong rigor that will allow investigators to delineate the sources of heterogeneity in the population with obesity. Collectively, we propose that it is critical to think of obesity as a heterogeneous disease with complex mechanisms and etiologies, requiring unique prevention and treatment strategies tailored to the individual.
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Affiliation(s)
| | - John E French
- Department of Nutrition, Gillings School of Global Public Health and School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA,Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - Naima Moustaid-Moussa
- Obesity Research Institute and Department of Nutritional Sciences, Texas Tech University, Lubbock, TX, USA
| | - Venkata S Voruganti
- Department of Nutrition, Gillings School of Global Public Health and School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA,Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - Elizabeth J Mayer-Davis
- Department of Nutrition, Gillings School of Global Public Health and School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Christopher A Bizon
- Renaissance Computing Institute, University of North Carolina at Chapel Hill, NC, USA
| | - Zhiyong Cheng
- Food Science and Human Nutrition Department, University of Florida, Gainesville, FL, USA
| | - Delisha A Stewart
- Department of Nutrition, Gillings School of Global Public Health and School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA,Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - John W Easterbrook
- Department of Nutrition, Gillings School of Global Public Health and School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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49
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Mishra B, Athar M, Mukhtar MS. Transcriptional circuitry atlas of genetic diverse unstimulated murine and human macrophages define disparity in population-wide innate immunity. Sci Rep 2021; 11:7373. [PMID: 33795737 PMCID: PMC8016976 DOI: 10.1038/s41598-021-86742-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 03/12/2021] [Indexed: 02/07/2023] Open
Abstract
Macrophages are ubiquitous custodians of tissues, which play decisive role in maintaining cellular homeostasis through regulatory immune responses. Within tissues, macrophage exhibit extremely heterogeneous population with varying functions orchestrated through regulatory response, which can be further exacerbated in diverse genetic backgrounds. Gene regulatory networks (GRNs) offer comprehensive understanding of cellular regulatory behavior by unfolding the transcription factors (TFs) and regulated target genes. RNA-Seq coupled with ATAC-Seq has revolutionized the regulome landscape influenced by gene expression modeling. Here, we employ an integrative multi-omics systems biology-based analysis and generated GRNs derived from the unstimulated bone marrow-derived macrophages of five inbred genetically defined murine strains, which are reported to be linked with most of the population-wide human genetic variants. Our probabilistic modeling of a basal hemostasis pan regulatory repertoire in diverse macrophages discovered 96 TFs targeting 6279 genes representing 468,291 interactions across five inbred murine strains. Subsequently, we identify core and distinctive GRN sub-networks in unstimulated macrophages to describe the system-wide conservation and dissimilarities, respectively across five murine strains. Our study concludes that discrepancies in unstimulated macrophage-specific regulatory networks not only drives the basal functional plasticity within genetic backgrounds, additionally aid in understanding the complexity of racial disparity among the human population during stress.
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Affiliation(s)
- Bharat Mishra
- Department of Biology, University of Alabama At Birmingham, 464 Campbell Hall, 1300 University Boulevard, Alabama, 35294, USA
| | - Mohammad Athar
- UAB Research Center of Excellence in Arsenicals, Department of Dermatology, School of Medicine, University of Alabama At Birmingham, Alabama, 35294, USA.
| | - M Shahid Mukhtar
- Department of Biology, University of Alabama At Birmingham, 464 Campbell Hall, 1300 University Boulevard, Alabama, 35294, USA. .,Nutrition Obesity Research Center, University of Alabama At Birmingham, 1675 University Blvd, Birmingham, AL, 35294, USA. .,Department of Surgery, University of Alabama At Birmingham, 1808 7th Ave S, Birmingham, AL, 35294, USA.
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50
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Integrative analysis of liver-specific non-coding regulatory SNPs associated with the risk of coronary artery disease. Am J Hum Genet 2021; 108:411-430. [PMID: 33626337 DOI: 10.1016/j.ajhg.2021.02.006] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 02/04/2021] [Indexed: 02/08/2023] Open
Abstract
Genetic factors underlying coronary artery disease (CAD) have been widely studied using genome-wide association studies (GWASs). However, the functional understanding of the CAD loci has been limited by the fact that a majority of GWAS variants are located within non-coding regions with no functional role. High cholesterol and dysregulation of the liver metabolism such as non-alcoholic fatty liver disease confer an increased risk of CAD. Here, we studied the function of non-coding single-nucleotide polymorphisms in CAD GWAS loci located within liver-specific enhancer elements by identifying their potential target genes using liver cis-eQTL analysis and promoter Capture Hi-C in HepG2 cells. Altogether, 734 target genes were identified of which 121 exhibited correlations to liver-related traits. To identify potentially causal regulatory SNPs, the allele-specific enhancer activity was analyzed by (1) sequence-based computational predictions, (2) quantification of allele-specific transcription factor binding, and (3) STARR-seq massively parallel reporter assay. Altogether, our analysis identified 1,277 unique SNPs that display allele-specific regulatory activity. Among these, susceptibility enhancers near important cholesterol homeostasis genes (APOB, APOC1, APOE, and LIPA) were identified, suggesting that altered gene regulatory activity could represent another way by which genetic variation regulates serum lipoprotein levels. Using CRISPR-based perturbation, we demonstrate how the deletion/activation of a single enhancer leads to changes in the expression of many target genes located in a shared chromatin interaction domain. Our integrative genomics approach represents a comprehensive effort in identifying putative causal regulatory regions and target genes that could predispose to clinical manifestation of CAD by affecting liver function.
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