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Allayee H, Farber CR, Seldin MM, Williams EG, James DE, Lusis AJ. Systems genetics approaches for understanding complex traits with relevance for human disease. eLife 2023; 12:e91004. [PMID: 37962168 PMCID: PMC10645424 DOI: 10.7554/elife.91004] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 10/16/2023] [Indexed: 11/15/2023] Open
Abstract
Quantitative traits are often complex because of the contribution of many loci, with further complexity added by environmental factors. In medical research, systems genetics is a powerful approach for the study of complex traits, as it integrates intermediate phenotypes, such as RNA, protein, and metabolite levels, to understand molecular and physiological phenotypes linking discrete DNA sequence variation to complex clinical and physiological traits. The primary purpose of this review is to describe some of the resources and tools of systems genetics in humans and rodent models, so that researchers in many areas of biology and medicine can make use of the data.
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Affiliation(s)
- Hooman Allayee
- Departments of Population & Public Health Sciences, University of Southern CaliforniaLos AngelesUnited States
- Biochemistry & Molecular Medicine, Keck School of Medicine, University of Southern CaliforniaLos AngelesUnited States
| | - Charles R Farber
- Center for Public Health Genomics, University of Virginia School of MedicineCharlottesvilleUnited States
- Departments of Biochemistry & Molecular Genetics, University of Virginia School of MedicineCharlottesvilleUnited States
- Public Health Sciences, University of Virginia School of MedicineCharlottesvilleUnited States
| | - Marcus M Seldin
- Department of Biological Chemistry, University of California, IrvineIrvineUnited States
| | - Evan Graehl Williams
- Luxembourg Centre for Systems Biomedicine, University of LuxembourgLuxembourgLuxembourg
| | - David E James
- School of Life and Environmental Sciences, University of SydneyCamperdownAustralia
- Faculty of Medicine and Health, University of SydneyCamperdownAustralia
- Charles Perkins Centre, University of SydneyCamperdownAustralia
| | - Aldons J Lusis
- Departments of Human Genetics, University of California, Los AngelesLos AngelesUnited States
- Medicine, University of California, Los AngelesLos AngelesUnited States
- Microbiology, Immunology, & Molecular Genetics, David Geffen School of Medicine of UCLALos AngelesUnited States
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2
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Masson SWC, Madsen S, Cooke KC, Potter M, Vegas AD, Carroll L, Thillainadesan S, Cutler HB, Walder KR, Cooney GJ, Morahan G, Stöckli J, James DE. Leveraging genetic diversity to identify small molecules that reverse mouse skeletal muscle insulin resistance. eLife 2023; 12:RP86961. [PMID: 37494090 PMCID: PMC10371229 DOI: 10.7554/elife.86961] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2023] Open
Abstract
Systems genetics has begun to tackle the complexity of insulin resistance by capitalising on computational advances to study high-diversity populations. 'Diversity Outbred in Australia (DOz)' is a population of genetically unique mice with profound metabolic heterogeneity. We leveraged this variance to explore skeletal muscle's contribution to whole-body insulin action through metabolic phenotyping and skeletal muscle proteomics of 215 DOz mice. Linear modelling identified 553 proteins that associated with whole-body insulin sensitivity (Matsuda Index) including regulators of endocytosis and muscle proteostasis. To enrich for causality, we refined this network by focusing on negatively associated, genetically regulated proteins, resulting in a 76-protein fingerprint of insulin resistance. We sought to perturb this network and restore insulin action with small molecules by integrating the Broad Institute Connectivity Map platform and in vitro assays of insulin action using the Prestwick chemical library. These complementary approaches identified the antibiotic thiostrepton as an insulin resistance reversal agent. Subsequent validation in ex vivo insulin-resistant mouse muscle and palmitate-induced insulin-resistant myotubes demonstrated potent insulin action restoration, potentially via upregulation of glycolysis. This work demonstrates the value of a drug-centric framework to validate systems-level analysis by identifying potential therapeutics for insulin resistance.
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Affiliation(s)
- Stewart W C Masson
- Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia
| | - Søren Madsen
- Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia
| | - Kristen C Cooke
- Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia
| | - Meg Potter
- Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia
| | - Alexis Diaz Vegas
- Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia
| | - Luke Carroll
- Australian Proteome Analysis Facility, Macquarie University, Macquarie Park, Australia
| | - Senthil Thillainadesan
- Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia
| | - Harry B Cutler
- Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia
| | - Ken R Walder
- School of Medicine, Deakin University, Geelong, Australia
| | - Gregory J Cooney
- Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia
| | - Grant Morahan
- Centre for Diabetes Research, Harry Perkins Institute of Medical Research, Murdoch, Australia
| | - Jacqueline Stöckli
- Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia
| | - David E James
- Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, Australia
- School of Medical Sciences University of Sydney, Sydney, Australia
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3
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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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4
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Does Therapeutic Repurposing in Cancer Meet the Expectations of Having Drugs at a Lower Price? Clin Drug Investig 2023; 43:227-239. [PMID: 36884210 PMCID: PMC10097740 DOI: 10.1007/s40261-023-01251-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/14/2023] [Indexed: 03/09/2023]
Abstract
Therapeutic repurposing emerged as an alternative to the traditional drug discovery and development model (DDD) of new molecular entities (NMEs). It was anticipated that by being faster, safer, and cheaper, the development would result in lower-cost drugs. As defined in this work, a repurposed cancer drug is one approved by a health regulatory authority against a non-cancer indication that then gains new approval for cancer. With this definition, only three drugs are repurposed for cancer: Bacillus Calmette-Guerin (BCG) vaccine (superficial bladder cancer, thalidomide [multiple myeloma], and propranolol [infantile hemangioma]). Each of these has a different history regarding price and affordability, and it is not yet possible to generalize the impact of drug repurposing on the final price to the patient. However, the development, including the price, does not differ significantly from an NME. For the end consumer, the product's price is unrelated to whether it followed the classical development or repurposing. Economic constraints for clinical development, and drug prescription biases for repurposing drugs, are barriers yet to be overcome. The affordability of cancer drugs is a complex issue that varies from country to country. Many alternatives for having affordable drugs have been put forward, however these measures have thus far failed and are, at best, palliative. There are no immediate solutions to the problem of access to cancer drugs. It is necessary to critically analyze the impact of the current drug development model and be creative in implementing new models that genuinely benefit society.
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5
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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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6
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Romo-Perez A, Dominguez-Gomez G, Chavez-Blanco A, Taja-Chayeb L, Gonzalez-Fierro A, Martinez EG, Correa-Basurto J, Duenas-Gonzalez A. BAPST. A Combo of Common use drugs as metabolic therapy of cancer-a theoretical proposal. Curr Mol Pharmacol 2021; 15:815-831. [PMID: 34620071 DOI: 10.2174/1874467214666211006123728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 08/16/2021] [Accepted: 09/01/2021] [Indexed: 12/24/2022]
Abstract
Advances in cancer therapy have yet to impact worldwide cancer mortality. Poor cancer drug affordability is one of the factors limiting mortality burden strikes. Up to now, cancer drug repurposing had no meet expectations concerning drug affordability. The three FDA-approved cancer drugs developed under repurposing -all-trans-retinoic acid, arsenic trioxide, and thalidomide- do not differ in price from other drugs developed under the classical model. Though additional factors affect the whole process from inception to commercialization, the repurposing of widely used, commercially available, and cheap drugs may help. This work reviews the concept of the malignant metabolic phenotype and its exploitation by simultaneously blocking key metabolic processes altered in cancer. We elaborate on a combination called BAPST, which stands for the following drugs and pathways they inhibit: Benserazide (glycolysis), Apomorphine (glutaminolysis), Pantoprazole (Fatty-acid synthesis), Simvastatin (mevalonate pathway), and Trimetazidine (Fatty-acid oxidation). Their respective primary indications are: • Parkinson's disease (benserazide and apomorphine). • Peptic ulcer disease (pantoprazole). • Hypercholesterolemia (simvastatin). • Ischemic heart disease (trimetazidine). When used for their primary indication, the literature review on each of these drugs shows they have a good safety profile and lack predicted pharmacokinetic interaction among them. Most importantly, the inhibitory enzymatic concentrations required for inhibiting their cancer targets enzymes are below the plasma concentrations observed when these drugs are used for their primary indication. Based on that, we propose that the regimen BAPTS merits preclinical testing.
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Affiliation(s)
- Adriana Romo-Perez
- Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico City. Mexico
| | | | - Alma Chavez-Blanco
- Subdirección de Investigación Básica, Instituto Nacional de Cancerología, Mexico City. Mexico
| | - Lucia Taja-Chayeb
- Subdirección de Investigación Básica, Instituto Nacional de Cancerología, Mexico City. Mexico
| | - Aurora Gonzalez-Fierro
- Subdirección de Investigación Básica, Instituto Nacional de Cancerología, Mexico City. Mexico
| | | | - Jose Correa-Basurto
- Laboratorio de Diseño y Desarrollo de Nuevos Fármacos e Innovación Biotecnológica, Escuela Superior de Medicina, Instituto Politécnico Nacional, Mexico City. Mexico
| | - Alfonso Duenas-Gonzalez
- Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico City. Mexico
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7
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König H, Frank D, Baumann M, Heil R. AI models and the future of genomic research and medicine: True sons of knowledge?: Artificial intelligence needs to be integrated with causal conceptions in biomedicine to harness its societal benefits for the field. Bioessays 2021; 43:e2100025. [PMID: 34382215 DOI: 10.1002/bies.202100025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 07/26/2021] [Accepted: 07/28/2021] [Indexed: 11/10/2022]
Abstract
The increasing availability of large-scale, complex data has made research into how human genomes determine physiology in health and disease, as well as its application to drug development and medicine, an attractive field for artificial intelligence (AI) approaches. Looking at recent developments, we explore how such approaches interconnect and may conflict with needs for and notions of causal knowledge in molecular genetics and genomic medicine. We provide reasons to suggest that-while capable of generating predictive knowledge at unprecedented pace and scale-if and how these approaches will be integrated with prevailing causal concepts will not only determine the future of scientific understanding and self-conceptions in these fields. But these questions will also be key to develop differentiated policies, such as for education and regulation, in order to harness societal benefits of AI for genomic research and medicine.
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Affiliation(s)
- Harald König
- Karlsruhe Institute of Technology, Institute for Technology Assessment and Systems Analysis (ITAS), Karlsruhe, Germany
| | - Daniel Frank
- Chair for Ethics, Theory, and History of the Life Sciences, University of Tübingen, Tübingen, Germany
| | - Martina Baumann
- Karlsruhe Institute of Technology, Institute for Technology Assessment and Systems Analysis (ITAS), Karlsruhe, Germany
| | - Reinhard Heil
- Karlsruhe Institute of Technology, Institute for Technology Assessment and Systems Analysis (ITAS), Karlsruhe, Germany
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8
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DeRaad DA, Cobos ME, Alkishe A, Ashraf U, Ahadji-Dabla KM, Nuñez-Penichet C, Peterson AT. Genome-environment association methods comparison supports omnigenic adaptation to ecological niche in malaria vector mosquitoes. Mol Ecol 2021; 30:6468-6485. [PMID: 34309095 DOI: 10.1111/mec.16094] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 07/02/2021] [Accepted: 07/19/2021] [Indexed: 11/29/2022]
Abstract
The concept of a fundamental ecological niche is central to questions of geographic distribution, population demography, species conservation, and evolutionary potential. However, robust inference of genomic regions associated with evolutionary adaptation to particular environmental conditions remains difficult due to the myriad of potential confounding processes that can generate heterogeneous patterns of variation across the genome. Here, we interrogate the potential role of genome environment association (GEA) testing as an initial step in building an understanding of the genetic basis of ecological niche. We leverage publicly available genomic data from the Anopheles gambiae 1000 Genomes (Ag1000g) Consortium to test the ability of multiple analytically unique GEA methods to handle confounding patterns of genetic variation, control false positive rates, and discern associations with broadly relevant climate variables from random allele frequency patterns throughout the genome. We found evidence supporting the ability of commonly implemented GEA methods to account for confounding patterns of spatial and genetic variation, and control false positive rates. However, we fail to find evidence supporting the ability of GEA tests to reject signals of adaptation to randomly simulated environmental variables, indicating that discerning between true signals of genome environment adaptation and genome environment correlations resulting from alternative evolutionary processes, remains challenging. Because signals of environmental adaptation are so diffuse and confounded throughout the genome, we argue that genomic adaptation to ecological niche is likely best understood under an omnigenic model wherein highly interconnected, genome-wide gene regulatory networks shape genomic adaptation to key environmental conditions.
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Affiliation(s)
- Devon A DeRaad
- Department of Ecology & Evolutionary Biology and Biodiversity Institute, University of Kansas, Lawrence, Kansas, USA
| | - Marlon E Cobos
- Department of Ecology & Evolutionary Biology and Biodiversity Institute, University of Kansas, Lawrence, Kansas, USA
| | - Abdelghafar Alkishe
- Department of Ecology & Evolutionary Biology and Biodiversity Institute, University of Kansas, Lawrence, Kansas, USA
| | - Uzma Ashraf
- Department of Environmental Sciences and Policy, Lahore School of Economics, Lahore, Pakistan
| | | | - Claudia Nuñez-Penichet
- Department of Ecology & Evolutionary Biology and Biodiversity Institute, University of Kansas, Lawrence, Kansas, USA
| | - A Townsend Peterson
- Department of Ecology & Evolutionary Biology and Biodiversity Institute, University of Kansas, Lawrence, Kansas, USA
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9
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Schcolnik-Cabrera A, Juárez-López D, Duenas-Gonzalez A. Perspectives on Drug Repurposing. Curr Med Chem 2021; 28:2085-2099. [PMID: 32867630 DOI: 10.2174/0929867327666200831141337] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Revised: 05/01/2020] [Accepted: 05/22/2020] [Indexed: 11/22/2022]
Abstract
Complex common diseases are a significant burden for our societies and demand not only preventive measures but also more effective, safer, and more affordable treatments. The whole process of the current model of drug discovery and development implies a high investment by the pharmaceutical industry, which ultimately impact in high drug prices. In this sense, drug repurposing would help meet the needs of patients to access useful and novel treatments. Unlike the traditional approach, drug repurposing enters both the preclinical evaluation and clinical trials of the compound of interest faster, budgeting research and development costs, and limiting potential biosafety risks. The participation of government, society, and private investors is needed to secure the funds for experimental design and clinical development of repurposing candidates to have affordable, effective, and safe repurposed drugs. Moreover, extensive advertising of repurposing as a concept in the health community, could reduce prescribing bias when enough clinical evidence exists, which will support the employment of cheaper and more accessible repurposed compounds for common conditions.
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Affiliation(s)
- Alejandro Schcolnik-Cabrera
- Departement de Biochimie et Medecine Moleculaire, Universite de Montreal, C.P. 6128, Succursale Centre- Ville, Montreal, QC, Canada
| | - Daniel Juárez-López
- Posgrado en Ciencias Biologicas, Universidad Nacional Autonoma de Mexico; Av. Ciudad Universitaria 3000, C.P. 04510, Coyoacan, Ciudad de Mexico, Mexico
| | - Alfonso Duenas-Gonzalez
- Division de Investigacion Basica, Instituto Nacional de Cancerologia, Ciudad de Mexico 14080, Mexico
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10
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Alvarez-Romero J, Voisin S, Eynon N, Hiam D. Mapping Robust Genetic Variants Associated with Exercise Responses. Int J Sports Med 2020; 42:3-18. [PMID: 32693428 DOI: 10.1055/a-1198-5496] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
This review summarised robust and consistent genetic variants associated with aerobic-related and resistance-related phenotypes. In total we highlight 12 SNPs and 7 SNPs that are robustly associated with variance in aerobic-related and resistance-related phenotypes respectively. To date, there is very little literature ascribed to understanding the interplay between genes and environmental factors and the development of physiological traits. We discuss future directions, including large-scale exercise studies to elucidate the functional relevance of the discovered genomic markers. This approach will allow more rigour and reproducible research in the field of exercise genomics.
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Affiliation(s)
| | - Sarah Voisin
- Institute for Health and Sport, Victoria University, Melbourne, Australia
| | - Nir Eynon
- Institute for Health and Sport, Victoria University, Melbourne, Australia.,MCRI, Murdoch Childrens Research Institute, Parkville, Australia
| | - Danielle Hiam
- Institute for Health and Sport, Victoria University, Melbourne, Australia
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11
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Pereira M, Ko JH, Logan J, Protheroe H, Kim KB, Tan ALM, Croucher PI, Park KS, Rotival M, Petretto E, Bassett JD, Williams GR, Behmoaras J. A trans-eQTL network regulates osteoclast multinucleation and bone mass. eLife 2020; 9:55549. [PMID: 32553114 PMCID: PMC7351491 DOI: 10.7554/elife.55549] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Accepted: 06/12/2020] [Indexed: 12/11/2022] Open
Abstract
Functional characterisation of cell-type-specific regulatory networks is key to establish a causal link between genetic variation and phenotype. The osteoclast offers a unique model for interrogating the contribution of co-regulated genes to in vivo phenotype as its multinucleation and resorption activities determine quantifiable skeletal traits. Here we took advantage of a trans-regulated gene network (MMnet, macrophage multinucleation network) which we found to be significantly enriched for GWAS variants associated with bone-related phenotypes. We found that the network hub gene Bcat1 and seven other co-regulated MMnet genes out of 13, regulate bone function. Specifically, global (Pik3cb-/-, Atp8b2+/-, Igsf8-/-, Eml1-/-, Appl2-/-, Deptor-/-) and myeloid-specific Slc40a1 knockout mice displayed abnormal bone phenotypes. We report opposing effects of MMnet genes on bone mass in mice and osteoclast multinucleation/resorption in humans with strong correlation between the two. These results identify MMnet as a functionally conserved network that regulates osteoclast multinucleation and bone mass.
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Affiliation(s)
- Marie Pereira
- Centre for Inflammatory Disease, Department of Immunology and Inflammation, Hammersmith Hospital, Imperial College London, London, United Kingdom.,Molecular Endocrinology Laboratory, Department of Metabolism, Digestion and Reproduction, Hammersmith Hospital, Imperial College London, London, United Kingdom
| | - Jeong-Hun Ko
- Centre for Inflammatory Disease, Department of Immunology and Inflammation, Hammersmith Hospital, Imperial College London, London, United Kingdom.,Molecular Endocrinology Laboratory, Department of Metabolism, Digestion and Reproduction, Hammersmith Hospital, Imperial College London, London, United Kingdom
| | - John Logan
- Molecular Endocrinology Laboratory, Department of Metabolism, Digestion and Reproduction, Hammersmith Hospital, Imperial College London, London, United Kingdom
| | - Hayley Protheroe
- Molecular Endocrinology Laboratory, Department of Metabolism, Digestion and Reproduction, Hammersmith Hospital, Imperial College London, London, United Kingdom
| | - Kee-Beom Kim
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, Charlottesville, United States
| | | | - Peter I Croucher
- The Garvan Institute of Medical Research and St. Vincent's Clinical School, University of NewSouth Wales Medicine, Sydney, Australia
| | - Kwon-Sik Park
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, Charlottesville, United States
| | - Maxime Rotival
- Human Evolutionary Genetics Unit, Institut Pasteur, Centre National de la Recherche Scientifique, UMR 2000, Paris, France
| | | | - Jh Duncan Bassett
- Molecular Endocrinology Laboratory, Department of Metabolism, Digestion and Reproduction, Hammersmith Hospital, Imperial College London, London, United Kingdom
| | - Graham R Williams
- Molecular Endocrinology Laboratory, Department of Metabolism, Digestion and Reproduction, Hammersmith Hospital, Imperial College London, London, United Kingdom
| | - Jacques Behmoaras
- Centre for Inflammatory Disease, Department of Immunology and Inflammation, Hammersmith Hospital, Imperial College London, London, United Kingdom
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12
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Abstract
Cardiovascular diseases are the leading cause of death worldwide. Complex diseases with highly heterogenous disease progression among patient populations, cardiovascular diseases feature multifactorial contributions from both genetic and environmental stressors. Despite significant effort utilizing multiple approaches from molecular biology to genome-wide association studies, the genetic landscape of cardiovascular diseases, particularly for the nonfamilial forms of heart failure, is still poorly understood. In the past decade, systems-level approaches based on omics technologies have become an important approach for the study of complex traits in large populations. These advances create opportunities to integrate genetic variation with other biological layers to identify and prioritize candidate genes, understand pathogenic pathways, and elucidate gene-gene and gene-environment interactions. In this review, we will highlight some of the recent progress made using systems genetics approaches to uncover novel mechanisms and molecular bases of cardiovascular pathophysiological manifestations. The key technology and data analysis platforms necessary to implement systems genetics will be described, and the current major challenges and future directions will also be discussed. For complex cardiovascular diseases, such as heart failure, systems genetics represents a powerful strategy to obtain mechanistic insights and to develop individualized diagnostic and therapeutic regiments, paving the way for precision cardiovascular medicine.
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Affiliation(s)
- Christoph D. Rau
- Departments of Anesthesiology, Medicine, Physiology
- Current address: Department of Genetics, University of North Carolina School of Medicine, Chapel Hill, NC 27599
| | - Aldons J. Lusis
- Department of Human Genetics and Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA 90095
| | - Yibin Wang
- Departments of Anesthesiology, Medicine, Physiology
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13
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Jan M, Gobet N, Diessler S, Franken P, Xenarios I. A multi-omics digital research object for the genetics of sleep regulation. Sci Data 2019; 6:258. [PMID: 31672980 PMCID: PMC6823400 DOI: 10.1038/s41597-019-0171-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Accepted: 07/26/2019] [Indexed: 12/24/2022] Open
Abstract
With the aim to uncover the molecular pathways underlying the regulation of sleep, we recently assembled an extensive and comprehensive systems genetics dataset interrogating a genetic reference population of mice at the levels of the genome, the brain and liver transcriptomes, the plasma metabolome, and the sleep-wake phenome. To facilitate a meaningful and efficient re-use of this public resource by others we designed, describe in detail, and made available a Digital Research Object (DRO), embedding data, documentation, and analytics. We present and discuss both the advantages and limitations of our multi-modal resource and analytic pipeline. The reproducibility of the results was tested by a bioinformatician not implicated in the original project and the robustness of results was assessed by re-annotating genetic and transcriptome data from the mm9 to the mm10 mouse genome assembly.
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Affiliation(s)
- Maxime Jan
- Centre for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Nastassia Gobet
- Centre for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
- Vital-IT, Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Shanaz Diessler
- Centre for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Paul Franken
- Centre for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Ioannis Xenarios
- Ludwig Cancer Research/CHUV-UNIL, Lausanne, Switzerland.
- Health 2030 Genome Center, Geneva, Switzerland.
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14
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Wray NR, Wijmenga C, Sullivan PF, Yang J, Visscher PM. Common Disease Is More Complex Than Implied by the Core Gene Omnigenic Model. Cell 2019; 173:1573-1580. [PMID: 29906445 DOI: 10.1016/j.cell.2018.05.051] [Citation(s) in RCA: 159] [Impact Index Per Article: 31.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2017] [Revised: 02/19/2018] [Accepted: 05/24/2018] [Indexed: 12/19/2022]
Abstract
The evidence that most adult-onset common diseases have a polygenic genetic architecture fully consistent with robust biological systems supported by multiple back-up mechanisms is now overwhelming. In this context, we consider the recent "omnigenic" or "core genes" model. A key assumption of the model is that there is a relatively small number of core genes relevant to any disease. While intuitively appealing, this model may underestimate the biological complexity of common disease, and therefore, the goal to discover core genes should not guide experimental design. We consider other implications of polygenicity, concluding that a focus on patient stratification is needed to achieve the goals of precision medicine.
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Affiliation(s)
- Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia; Queensland Brain Institute, The University of Queensland, Brisbane, Australia.
| | - Cisca Wijmenga
- University of Groningen, University Medical Center Groningen, Department of Genetics, P.O. Box 30001, 9700 RB Groningen, Netherlands
| | - Patrick F Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jian Yang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia; Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia; Queensland Brain Institute, The University of Queensland, Brisbane, Australia
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15
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Bagnati M, Moreno-Moral A, Ko JH, Nicod J, Harmston N, Imprialou M, Game L, Gil J, Petretto E, Behmoaras J. Systems genetics identifies a macrophage cholesterol network associated with physiological wound healing. JCI Insight 2019; 4:e125736. [PMID: 30674726 PMCID: PMC6413785 DOI: 10.1172/jci.insight.125736] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Accepted: 12/18/2018] [Indexed: 01/18/2023] Open
Abstract
Among other cells, macrophages regulate the inflammatory and reparative phases during wound healing but genetic determinants and detailed molecular pathways that modulate these processes are not fully elucidated. Here, we took advantage of normal variation in wound healing in 1,378 genetically outbred mice, and carried out macrophage RNA-sequencing profiling of mice with extreme wound healing phenotypes (i.e., slow and fast healers, n = 146 in total). The resulting macrophage coexpression networks were genetically mapped and led to the identification of a unique module under strong trans-acting genetic control by the Runx2 locus. This macrophage-mediated healing network was specifically enriched for cholesterol and fatty acid biosynthetic processes. Pharmacological blockage of fatty acid synthesis with cerulenin resulted in delayed wound healing in vivo, and increased macrophage infiltration in the wounded skin, suggesting the persistence of an unresolved inflammation. We show how naturally occurring sequence variation controls transcriptional networks in macrophages, which in turn regulate specific metabolic pathways that could be targeted in wound healing.
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Affiliation(s)
- Marta Bagnati
- Centre for Inflammatory Disease, Imperial College London, Hammersmith Hospital, London, United Kingdom (UK)
| | | | - Jeong-Hun Ko
- Centre for Inflammatory Disease, Imperial College London, Hammersmith Hospital, London, United Kingdom (UK)
| | - Jérôme Nicod
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | - Martha Imprialou
- Centre for Inflammatory Disease, Imperial College London, Hammersmith Hospital, London, United Kingdom (UK)
| | - Laurence Game
- Genomics Laboratory, Medical Research Council (MRC) London Institute of Medical Sciences, Imperial College London, Hammersmith Hospital, London, UK
| | - Jesus Gil
- Cell Proliferation Group, MRC London Institute of Medical Sciences (LMS), London, UK
| | - Enrico Petretto
- Duke-NUS Medical School, Singapore, Singapore
- MRC London Institute of Medical Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Jacques Behmoaras
- Centre for Inflammatory Disease, Imperial College London, Hammersmith Hospital, London, United Kingdom (UK)
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16
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Diessler S, Jan M, Emmenegger Y, Guex N, Middleton B, Skene DJ, Ibberson M, Burdet F, Götz L, Pagni M, Sankar M, Liechti R, Hor CN, Xenarios I, Franken P. A systems genetics resource and analysis of sleep regulation in the mouse. PLoS Biol 2018; 16:e2005750. [PMID: 30091978 PMCID: PMC6085075 DOI: 10.1371/journal.pbio.2005750] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2018] [Accepted: 07/06/2018] [Indexed: 12/30/2022] Open
Abstract
Sleep is essential for optimal brain functioning and health, but the biological substrates through which sleep delivers these beneficial effects remain largely unknown. We used a systems genetics approach in the BXD genetic reference population (GRP) of mice and assembled a comprehensive experimental knowledge base comprising a deep "sleep-wake" phenome, central and peripheral transcriptomes, and plasma metabolome data, collected under undisturbed baseline conditions and after sleep deprivation (SD). We present analytical tools to interactively interrogate the database, visualize the molecular networks altered by sleep loss, and prioritize candidate genes. We found that a one-time, short disruption of sleep already extensively reshaped the systems genetics landscape by altering 60%-78% of the transcriptomes and the metabolome, with numerous genetic loci affecting the magnitude and direction of change. Systems genetics integrative analyses drawing on all levels of organization imply α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor trafficking and fatty acid turnover as substrates of the negative effects of insufficient sleep. Our analyses demonstrate that genetic heterogeneity and the effects of insufficient sleep itself on the transcriptome and metabolome are far more widespread than previously reported.
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Affiliation(s)
- Shanaz Diessler
- Center for Integrative Genomics, University of Lausanne, Switzerland
| | - Maxime Jan
- Center for Integrative Genomics, University of Lausanne, Switzerland
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Yann Emmenegger
- Center for Integrative Genomics, University of Lausanne, Switzerland
| | - Nicolas Guex
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Benita Middleton
- Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | - Debra J. Skene
- Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | - Mark Ibberson
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Frederic Burdet
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Lou Götz
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Marco Pagni
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Martial Sankar
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Robin Liechti
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Charlotte N. Hor
- Center for Integrative Genomics, University of Lausanne, Switzerland
| | - Ioannis Xenarios
- Center for Integrative Genomics, University of Lausanne, Switzerland
- Vital-IT Systems Biology Division, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Paul Franken
- Center for Integrative Genomics, University of Lausanne, Switzerland
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17
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Pan J, Meyers RM, Michel BC, Mashtalir N, Sizemore AE, Wells JN, Cassel SH, Vazquez F, Weir BA, Hahn WC, Marsh JA, Tsherniak A, Kadoch C. Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens. Cell Syst 2018; 6:555-568.e7. [PMID: 29778836 DOI: 10.1016/j.cels.2018.04.011] [Citation(s) in RCA: 92] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Revised: 04/03/2018] [Accepted: 04/24/2018] [Indexed: 11/15/2022]
Abstract
Protein complexes are assemblies of subunits that have co-evolved to execute one or many coordinated functions in the cellular environment. Functional annotation of mammalian protein complexes is critical to understanding biological processes, as well as disease mechanisms. Here, we used genetic co-essentiality derived from genome-scale RNAi- and CRISPR-Cas9-based fitness screens performed across hundreds of human cancer cell lines to assign measures of functional similarity. From these measures, we systematically built and characterized functional similarity networks that recapitulate known structural and functional features of well-studied protein complexes and resolve novel functional modules within complexes lacking structural resolution, such as the mammalian SWI/SNF complex. Finally, by integrating functional networks with large protein-protein interaction networks, we discovered novel protein complexes involving recently evolved genes of unknown function. Taken together, these findings demonstrate the utility of genetic perturbation screens alone, and in combination with large-scale biophysical data, to enhance our understanding of mammalian protein complexes in normal and disease states.
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Affiliation(s)
- Joshua Pan
- Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA; Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA; Biomedical and Biological Sciences Program, Harvard Medical School, Boston, MA 02115, USA
| | - Robin M Meyers
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
| | - Brittany C Michel
- Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA; Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA; Biomedical and Biological Sciences Program, Harvard Medical School, Boston, MA 02115, USA
| | - Nazar Mashtalir
- Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA; Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
| | - Ann E Sizemore
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
| | - Jonathan N Wells
- MRC Human Genetics Unit, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Seth H Cassel
- Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA; Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA; Biomedical and Biological Sciences Program, Harvard Medical School, Boston, MA 02115, USA; Medical Scientist Training Program, Harvard Medical School, Boston, MA 02115, USA
| | - Francisca Vazquez
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
| | - Barbara A Weir
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
| | - William C Hahn
- Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA; Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA; Harvard Medical School, Boston, MA 02115, USA; Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Joseph A Marsh
- MRC Human Genetics Unit, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Aviad Tsherniak
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
| | - Cigall Kadoch
- Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA; Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA; Harvard Medical School, Boston, MA 02115, USA.
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18
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Protein Moonlighting Revealed by Noncatalytic Phenotypes of Yeast Enzymes. Genetics 2017; 208:419-431. [PMID: 29127264 DOI: 10.1534/genetics.117.300377] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Accepted: 11/06/2017] [Indexed: 12/19/2022] Open
Abstract
A single gene can partake in several biological processes, and therefore gene deletions can lead to different-sometimes unexpected-phenotypes. However, it is not always clear whether such pleiotropy reflects the loss of a unique molecular activity involved in different processes or the loss of a multifunctional protein. Here, using Saccharomyces cerevisiae metabolism as a model, we systematically test the null hypothesis that enzyme phenotypes depend on a single annotated molecular function, namely their catalysis. We screened a set of carefully selected genes by quantifying the contribution of catalysis to gene deletion phenotypes under different environmental conditions. While most phenotypes were explained by loss of catalysis, slow growth was readily rescued by a catalytically inactive protein in about one-third of the enzymes tested. Such noncatalytic phenotypes were frequent in the Alt1 and Bat2 transaminases and in the isoleucine/valine biosynthetic enzymes Ilv1 and Ilv2, suggesting novel "moonlighting" activities in these proteins. Furthermore, differential genetic interaction profiles of gene deletion and catalytic mutants indicated that ILV1 is functionally associated with regulatory processes, specifically to chromatin modification. Our systematic study shows that gene loss phenotypes and their genetic interactions are frequently not driven by the loss of an annotated catalytic function, underscoring the moonlighting nature of cellular metabolism.
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