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Moreno P, Fexova S, George N, Manning JR, Miao Z, Mohammed S, Muñoz-Pomer A, Fullgrabe A, Bi Y, Bush N, Iqbal H, Kumbham U, Solovyev A, Zhao L, Prakash A, García-Seisdedos D, Kundu DJ, Wang S, Walzer M, Clarke L, Osumi-Sutherland D, Tello-Ruiz MK, Kumari S, Ware D, Eliasova J, Arends MJ, Nawijn MC, Meyer K, Burdett T, Marioni J, Teichmann S, Vizcaíno JA, Brazma A, Papatheodorou I. Expression Atlas update: gene and protein expression in multiple species. Nucleic Acids Res 2022; 50:D129-D140. [PMID: 34850121 PMCID: PMC8728300 DOI: 10.1093/nar/gkab1030] [Citation(s) in RCA: 63] [Impact Index Per Article: 31.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 10/11/2021] [Accepted: 11/19/2021] [Indexed: 01/21/2023] Open
Abstract
The EMBL-EBI Expression Atlas is an added value knowledge base that enables researchers to answer the question of where (tissue, organism part, developmental stage, cell type) and under which conditions (disease, treatment, gender, etc) a gene or protein of interest is expressed. Expression Atlas brings together data from >4500 expression studies from >65 different species, across different conditions and tissues. It makes these data freely available in an easy to visualise form, after expert curation to accurately represent the intended experimental design, re-analysed via standardised pipelines that rely on open-source community developed tools. Each study's metadata are annotated using ontologies. The data are re-analyzed with the aim of reproducing the original conclusions of the underlying experiments. Expression Atlas is currently divided into Bulk Expression Atlas and Single Cell Expression Atlas. Expression Atlas contains data from differential studies (microarray and bulk RNA-Seq) and baseline studies (bulk RNA-Seq and proteomics), whereas Single Cell Expression Atlas is currently dedicated to Single Cell RNA-Sequencing (scRNA-Seq) studies. The resource has been in continuous development since 2009 and it is available at https://www.ebi.ac.uk/gxa.
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Affiliation(s)
- Pablo Moreno
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Silvie Fexova
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Nancy George
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Jonathan R Manning
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Zhichiao Miao
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Suhaib Mohammed
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Alfonso Muñoz-Pomer
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Anja Fullgrabe
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Yalan Bi
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Natassja Bush
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Haider Iqbal
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Upendra Kumbham
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Andrey Solovyev
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Lingyun Zhao
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Ananth Prakash
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - David García-Seisdedos
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Deepti J Kundu
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Shengbo Wang
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Mathias Walzer
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Laura Clarke
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - David Osumi-Sutherland
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | | | - Sunita Kumari
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Doreen Ware
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
- USDA ARS NEA, Plant Soil & Nutrition Laboratory Research Unit, Ithaca, NY 14853, USA
| | - Jana Eliasova
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Mark J Arends
- Edinburgh Pathology, University of Edinburgh, Institute of Genetics & Cancer, Edinburgh, UK
| | - Martijn C Nawijn
- Department of Pathology and Medical Biology, GRIAC research institute, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Kerstin Meyer
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Tony Burdett
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - John Marioni
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Sarah Teichmann
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Alvis Brazma
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
| | - Irene Papatheodorou
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
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2
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Kerimov N, Hayhurst JD, Peikova K, Manning JR, Walter P, Kolberg L, Samoviča M, Sakthivel MP, Kuzmin I, Trevanion SJ, Burdett T, Jupp S, Parkinson H, Papatheodorou I, Yates AD, Zerbino DR, Alasoo K. A compendium of uniformly processed human gene expression and splicing quantitative trait loci. Nat Genet 2021; 53:1290-1299. [PMID: 34493866 PMCID: PMC8423625 DOI: 10.1038/s41588-021-00924-w] [Citation(s) in RCA: 128] [Impact Index Per Article: 42.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 07/26/2021] [Indexed: 12/15/2022]
Abstract
Many gene expression quantitative trait locus (eQTL) studies have published their summary statistics, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and co-localization. However, technical differences between these datasets are a barrier to their widespread use. Consequently, target genes for most genome-wide association study (GWAS) signals have still not been identified. In the present study, we present the eQTL Catalogue ( https://www.ebi.ac.uk/eqtl ), a resource of quality-controlled, uniformly re-computed gene expression and splicing QTLs from 21 studies. We find that, for matching cell types and tissues, the eQTL effect sizes are highly reproducible between studies. Although most QTLs were shared between most bulk tissues, we identified a greater diversity of cell-type-specific QTLs from purified cell types, a subset of which also manifested as new disease co-localizations. Our summary statistics are freely available to enable the systematic interpretation of human GWAS associations across many cell types and tissues.
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Affiliation(s)
- Nurlan Kerimov
- Institute of Computer Science, University of Tartu, Tartu, Estonia
- Open Targets, Wellcome Genome Campus, Cambridge, UK
| | - James D Hayhurst
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Kateryna Peikova
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Jonathan R Manning
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Peter Walter
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Liis Kolberg
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Marija Samoviča
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Manoj Pandian Sakthivel
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Ivan Kuzmin
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Stephen J Trevanion
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Tony Burdett
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Simon Jupp
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Helen Parkinson
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Irene Papatheodorou
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Andrew D Yates
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Daniel R Zerbino
- Open Targets, Wellcome Genome Campus, Cambridge, UK.
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK.
| | - Kaur Alasoo
- Institute of Computer Science, University of Tartu, Tartu, Estonia.
- Open Targets, Wellcome Genome Campus, Cambridge, UK.
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3
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Tekman M, Batut B, Ostrovsky A, Antoniewski C, Clements D, Ramirez F, Etherington GJ, Hotz HR, Scholtalbers J, Manning JR, Bellenger L, Doyle MA, Heydarian M, Huang N, Soranzo N, Moreno P, Mautner S, Papatheodorou I, Nekrutenko A, Taylor J, Blankenberg D, Backofen R, Grüning B. A single-cell RNA-sequencing training and analysis suite using the Galaxy framework. Gigascience 2020; 9:5931798. [PMID: 33079170 PMCID: PMC7574357 DOI: 10.1093/gigascience/giaa102] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 08/30/2020] [Indexed: 11/25/2022] Open
Abstract
Background The vast ecosystem of single-cell RNA-sequencing tools has until recently been plagued by an excess of diverging analysis strategies, inconsistent file formats, and compatibility issues between different software suites. The uptake of 10x Genomics datasets has begun to calm this diversity, and the bioinformatics community leans once more towards the large computing requirements and the statistically driven methods needed to process and understand these ever-growing datasets. Results Here we outline several Galaxy workflows and learning resources for single-cell RNA-sequencing, with the aim of providing a comprehensive analysis environment paired with a thorough user learning experience that bridges the knowledge gap between the computational methods and the underlying cell biology. The Galaxy reproducible bioinformatics framework provides tools, workflows, and trainings that not only enable users to perform 1-click 10x preprocessing but also empower them to demultiplex raw sequencing from custom tagged and full-length sequencing protocols. The downstream analysis supports a range of high-quality interoperable suites separated into common stages of analysis: inspection, filtering, normalization, confounder removal, and clustering. The teaching resources cover concepts from computer science to cell biology. Access to all resources is provided at the singlecell.usegalaxy.eu portal. Conclusions The reproducible and training-oriented Galaxy framework provides a sustainable high-performance computing environment for users to run flexible analyses on both 10x and alternative platforms. The tutorials from the Galaxy Training Network along with the frequent training workshops hosted by the Galaxy community provide a means for users to learn, publish, and teach single-cell RNA-sequencing analysis.
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Affiliation(s)
- Mehmet Tekman
- Department of Bioinformatics, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany
| | - Bérénice Batut
- Department of Bioinformatics, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany
| | - Alexander Ostrovsky
- Department of Biology, Johns Hopkins University, Mudd Hall 144, 3400 N. Charles Street, Baltimore, MD 21218, USA
| | - Christophe Antoniewski
- ARTbio, Sorbonne Université, CNRS FR 3631, Inserm US 037, Paris, France.,Institut de Biologie Paris Seine, 9 Quai Saint-Bernard Université Pierre et Marie Curie, Campus Jussieu, Bâtiments A-B-C, 75005 Paris, France
| | - Dave Clements
- Department of Biology, Johns Hopkins University, Mudd Hall 144, 3400 N. Charles Street, Baltimore, MD 21218, USA
| | - Fidel Ramirez
- Boehringer Ingelheim International GmbH, Binger Strasse 173, 55216 Ingelheim am Rhein, Biberach, Germany
| | | | - Hans-Rudolf Hotz
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, 4058 Basel, Switzerland.,SIB Swiss Institute of Bioinformatics, Maulbeerstrasse 66, 4058 Basel, Switzerland
| | - Jelle Scholtalbers
- European Molecular Biology Laboratory, Genome Biology Unit, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Jonathan R Manning
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Lea Bellenger
- ARTbio, Sorbonne Université, CNRS FR 3631, Inserm US 037, Paris, France
| | - Maria A Doyle
- Research Computing Facility, Peter MacCallum Cancer Centre, Melbourne, 305 Grattan Street, Victoria 3000, Australia.,Sir Peter MacCallum Department of Oncology, The University of Melbourne, Victoria 3010, Australia
| | - Mohammad Heydarian
- Department of Biology, Johns Hopkins University, Mudd Hall 144, 3400 N. Charles Street, Baltimore, MD 21218, USA
| | - Ni Huang
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK.,Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK
| | - Nicola Soranzo
- Earlham Institute, Norwich Research Park, Norwich NR4 7UZ, UK
| | - Pablo Moreno
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Stefan Mautner
- Department of Bioinformatics, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany
| | - Irene Papatheodorou
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Anton Nekrutenko
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | - James Taylor
- Department of Biology, Johns Hopkins University, Mudd Hall 144, 3400 N. Charles Street, Baltimore, MD 21218, USA
| | - Daniel Blankenberg
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, NB21 Cleveland, OH 44195, USA
| | - Rolf Backofen
- Department of Bioinformatics, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany
| | - Björn Grüning
- Department of Bioinformatics, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany
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4
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Ruetz T, Pfisterer U, Di Stefano B, Ashmore J, Beniazza M, Tian TV, Kaemena DF, Tosti L, Tan W, Manning JR, Chantzoura E, Ottosson DR, Collombet S, Johnsson A, Cohen E, Yusa K, Linnarsson S, Graf T, Parmar M, Kaji K. Constitutively Active SMAD2/3 Are Broad-Scope Potentiators of Transcription-Factor-Mediated Cellular Reprogramming. Cell Stem Cell 2017; 21:791-805.e9. [PMID: 29174331 PMCID: PMC5732323 DOI: 10.1016/j.stem.2017.10.013] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2016] [Revised: 07/17/2017] [Accepted: 10/25/2017] [Indexed: 02/06/2023]
Abstract
Reprogramming of cellular identity using exogenous expression of transcription factors (TFs) is a powerful and exciting tool for tissue engineering, disease modeling, and regenerative medicine. However, generation of desired cell types using this approach is often plagued by inefficiency, slow conversion, and an inability to produce mature functional cells. Here, we show that expression of constitutively active SMAD2/3 significantly improves the efficiency of induced pluripotent stem cell (iPSC) generation by the Yamanaka factors. Mechanistically, SMAD3 interacts with reprogramming factors and co-activators and co-occupies OCT4 target loci during reprogramming. Unexpectedly, active SMAD2/3 also markedly enhances three other TF-mediated direct reprogramming conversions, from B cells to macrophages, myoblasts to adipocytes, and human fibroblasts to neurons, highlighting broad and general roles for SMAD2/3 as cell-reprogramming potentiators. Our results suggest that co-expression of active SMAD2/3 could enhance multiple types of TF-based cell identity conversion and therefore be a powerful tool for cellular engineering.
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Affiliation(s)
- Tyson Ruetz
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh BioQuarter, 5 Little France Drive, Edinburgh EH16 4UU, Scotland, UK
| | - Ulrich Pfisterer
- Department of Experimental Medical Science, Developmental and Regenerative Neurobiology, Wallenberg Neuroscience Center and Lund Stem Cell Center, Lund University, 22184 Lund, Sweden
| | - Bruno Di Stefano
- Centre for Genomic Regulation, Dr Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003 Barcelona, Spain
| | - James Ashmore
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh BioQuarter, 5 Little France Drive, Edinburgh EH16 4UU, Scotland, UK
| | - Meryam Beniazza
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh BioQuarter, 5 Little France Drive, Edinburgh EH16 4UU, Scotland, UK
| | - Tian V Tian
- Centre for Genomic Regulation, Dr Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003 Barcelona, Spain
| | - Daniel F Kaemena
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh BioQuarter, 5 Little France Drive, Edinburgh EH16 4UU, Scotland, UK
| | - Luca Tosti
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh BioQuarter, 5 Little France Drive, Edinburgh EH16 4UU, Scotland, UK
| | - Wenfang Tan
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh BioQuarter, 5 Little France Drive, Edinburgh EH16 4UU, Scotland, UK
| | - Jonathan R Manning
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh BioQuarter, 5 Little France Drive, Edinburgh EH16 4UU, Scotland, UK
| | - Eleni Chantzoura
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh BioQuarter, 5 Little France Drive, Edinburgh EH16 4UU, Scotland, UK
| | - Daniella Rylander Ottosson
- Department of Experimental Medical Science, Developmental and Regenerative Neurobiology, Wallenberg Neuroscience Center and Lund Stem Cell Center, Lund University, 22184 Lund, Sweden
| | - Samuel Collombet
- Institut de Biologie de l'Ecole Normale Supérieure, CNRS UMR8197, INSERM U1024, 75005 Paris, France
| | - Anna Johnsson
- Laboratory for Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institute, Scheeles väg 1, SE-171 77 Stockholm, Sweden
| | - Erez Cohen
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh BioQuarter, 5 Little France Drive, Edinburgh EH16 4UU, Scotland, UK
| | - Kosuke Yusa
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Sten Linnarsson
- Laboratory for Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institute, Scheeles väg 1, SE-171 77 Stockholm, Sweden
| | - Thomas Graf
- Centre for Genomic Regulation, Dr Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003 Barcelona, Spain; The Barcelona Institute of Science and Technology, Carrer del Comte d'Urgell 187, Building 12 (BIST), 08036 Barcelona, Spain
| | - Malin Parmar
- Department of Experimental Medical Science, Developmental and Regenerative Neurobiology, Wallenberg Neuroscience Center and Lund Stem Cell Center, Lund University, 22184 Lund, Sweden
| | - Keisuke Kaji
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh BioQuarter, 5 Little France Drive, Edinburgh EH16 4UU, Scotland, UK.
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5
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Moore JK, MacKinnon AC, Man TY, Manning JR, Forbes SJ, Simpson KJ. Patients with the worst outcomes after paracetamol (acetaminophen)-induced liver failure have an early monocytopenia. Aliment Pharmacol Ther 2017; 45:443-454. [PMID: 27896824 DOI: 10.1111/apt.13878] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2016] [Revised: 09/21/2016] [Accepted: 11/04/2016] [Indexed: 12/12/2022]
Abstract
BACKGROUND Acute liver failure (ALF) is associated with significant morbidity and mortality. Studies have implicated the immune response, especially monocyte/macrophages as being important in dictating outcome. AIM To investigate changes in the circulating monocytes and other immune cells serially in patients with ALF, relate these with cytokine concentrations, monocyte gene expression and patient outcome. METHODS In a prospective case-control study in the Scottish Liver Transplant Unit, Royal Infirmary Edinburgh, 35 consecutive patients admitted with paracetamol-induced liver failure (POD-ALF), 10 patients with non-paracetamol causes of ALF and 16 controls were recruited. The peripheral blood monocyte phenotype was analysed by flow cytometry, circulating cytokines quantified by protein array and monocyte gene expression array performed and related to outcome. RESULTS On admission, patients with worst outcomes after POD-ALF had a significant monocytopenia, characterised by reduced classical and expanded intermediate monocyte population. This was associated with reduced circulating lymphocytes and natural killer cells, peripheral cytokine patterns suggestive of a 'cytokine storm' and increased concentrations of cytokines associated with monocyte egress from the bone marrow. Gene expression array did not differentiate patient outcome. At day 4, there was no significant difference in monocyte, lymphocyte or natural killer cells between survivors and the patients with adverse outcomes. CONCLUSIONS Severe paracetamol liver failure is associated with profound changes in the peripheral blood compartment, particularly in monocytes, related with worse outcomes. This is not seen in patients with non-paracetamol-induced liver failure. Significant monocytopenia on admission may allow earlier clarification of prognosis, and it highlights a potential target for therapeutic intervention.
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Affiliation(s)
- J K Moore
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, UK
| | - A C MacKinnon
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, UK
| | - T Y Man
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, UK
| | - J R Manning
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, UK
| | - S J Forbes
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, UK
| | - K J Simpson
- Division of Clinical and Surgical Sciences, University of Edinburgh, Edinburgh, UK
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6
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Yeung ENW, Treskes P, Martin SF, Manning JR, Dunbar DR, Rogers SM, Le Bihan T, Lockman KA, Morley SD, Hayes PC, Nelson LJ, Plevris JN. Erratum to: Fibrinogen production is enhanced in an in-vitro model of non-alcoholic fatty liver disease: an isolated risk factor for cardiovascular events? Lipids Health Dis 2016; 15:125. [PMID: 27480541 PMCID: PMC4970298 DOI: 10.1186/s12944-016-0290-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Affiliation(s)
- Emily N W Yeung
- Hepatology Laboratory, Division of Health Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
| | - Philipp Treskes
- Hepatology Laboratory, Division of Health Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - Sarah F Martin
- Kinetic Parameter Facility, SynthSys, Centre for Synthetic and Systems Biology, University of Edinburgh, C.H. Waddington Building, The Kings Buildings, Edinburgh, EH9 3JD, UK
| | - Jonathan R Manning
- Bioinformatics Team, University/BHF Centre for Cardiovascular Science, University of Edinburgh, Queen's Medical Research Institute, 47 Little France Crescent, Edinburgh, EH16 4TJ, UK
| | - Donald R Dunbar
- Bioinformatics Team, University/BHF Centre for Cardiovascular Science, University of Edinburgh, Queen's Medical Research Institute, 47 Little France Crescent, Edinburgh, EH16 4TJ, UK
| | - Sophie M Rogers
- Kinetic Parameter Facility, SynthSys, Centre for Synthetic and Systems Biology, University of Edinburgh, C.H. Waddington Building, The Kings Buildings, Edinburgh, EH9 3JD, UK
| | - Thierry Le Bihan
- Kinetic Parameter Facility, SynthSys, Centre for Synthetic and Systems Biology, University of Edinburgh, C.H. Waddington Building, The Kings Buildings, Edinburgh, EH9 3JD, UK
| | - K Ann Lockman
- Hepatology Laboratory, Division of Health Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - Steven D Morley
- Hepatology Laboratory, Division of Health Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - Peter C Hayes
- Hepatology Laboratory, Division of Health Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - Leonard J Nelson
- Hepatology Laboratory, Division of Health Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - John N Plevris
- Hepatology Laboratory, Division of Health Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
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7
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Betz BB, Jenks SJ, Cronshaw AD, Lamont DJ, Cairns C, Manning JR, Goddard J, Webb DJ, Mullins JJ, Hughes J, McLachlan S, Strachan MW, Price JF, Conway BR. Urinary peptidomics in a rodent model of diabetic nephropathy highlights epidermal growth factor as a biomarker for renal deterioration in patients with type 2 diabetes. Kidney Int 2016; 89:1125-1135. [DOI: 10.1016/j.kint.2016.01.015] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2015] [Revised: 01/03/2016] [Accepted: 01/07/2016] [Indexed: 12/26/2022]
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8
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Khulan B, Liu L, Rose CM, Boyle AK, Manning JR, Drake AJ. Glucocorticoids accelerate maturation of the heme pathway in fetal liver through effects on transcription and DNA methylation. Epigenetics 2016; 11:103-9. [PMID: 26889791 PMCID: PMC4846099 DOI: 10.1080/15592294.2016.1144006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Glucocorticoids are widely used in threatened preterm labor to promote maturation in many organ systems in preterm babies and have significant beneficial effects on morbidity and mortality. We performed transcriptional profiling in fetal liver in a rat model of prenatal glucocorticoid exposure and identified marked gene expression changes in heme biosynthesis, utilization, and degradation pathways in late gestation. These changes in gene expression associated with alterations in DNA methylation and with a reduction in hepatic heme concentration. There were no persistent differences in gene expression, DNA methylation, or heme concentrations at 4 weeks of age, suggesting that these are transient effects. Our findings are consistent with glucocorticoid-induced accelerated maturation of the haematopoietic system and support the hypothesis that glucocorticoids can drive changes in gene expression in association with alterations in DNA methylation.
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Affiliation(s)
- Batbayar Khulan
- a University/BHF Center for Cardiovascular Science, University of Edinburgh, Queen's Medical Research Institute , 47 Little France Crescent, Edinburgh , UK
| | - Lincoln Liu
- a University/BHF Center for Cardiovascular Science, University of Edinburgh, Queen's Medical Research Institute , 47 Little France Crescent, Edinburgh , UK
| | - Catherine M Rose
- a University/BHF Center for Cardiovascular Science, University of Edinburgh, Queen's Medical Research Institute , 47 Little France Crescent, Edinburgh , UK
| | - Ashley K Boyle
- a University/BHF Center for Cardiovascular Science, University of Edinburgh, Queen's Medical Research Institute , 47 Little France Crescent, Edinburgh , UK
| | - Jonathan R Manning
- a University/BHF Center for Cardiovascular Science, University of Edinburgh, Queen's Medical Research Institute , 47 Little France Crescent, Edinburgh , UK
| | - Amanda J Drake
- a University/BHF Center for Cardiovascular Science, University of Edinburgh, Queen's Medical Research Institute , 47 Little France Crescent, Edinburgh , UK
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Sparrow S, Manning JR, Cartier J, Anblagan D, Bastin ME, Piyasena C, Pataky R, Moore EJ, Semple SI, Wilkinson AG, Evans M, Drake AJ, Boardman JP. Epigenomic profiling of preterm infants reveals DNA methylation differences at sites associated with neural function. Transl Psychiatry 2016; 6:e716. [PMID: 26784970 PMCID: PMC5068883 DOI: 10.1038/tp.2015.210] [Citation(s) in RCA: 62] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2015] [Revised: 11/18/2015] [Accepted: 11/19/2015] [Indexed: 12/13/2022] Open
Abstract
DNA methylation (DNAm) plays a determining role in neural cell fate and provides a molecular link between early-life stress and neuropsychiatric disease. Preterm birth is a profound environmental stressor that is closely associated with alterations in connectivity of neural systems and long-term neuropsychiatric impairment. The aims of this study were to examine the relationship between preterm birth and DNAm, and to investigate factors that contribute to variance in DNAm. DNA was collected from preterm infants (birth<33 weeks gestation) and healthy controls (birth>37 weeks), and a genome-wide analysis of DNAm was performed; diffusion magnetic resonance imaging (dMRI) data were acquired from the preterm group. The major fasciculi were segmented, and fractional anisotropy, mean diffusivity and tract shape were calculated. Principal components (PC) analysis was used to investigate the contribution of MRI features and clinical variables to variance in DNAm. Differential methylation was found within 25 gene bodies and 58 promoters of protein-coding genes in preterm infants compared with controls; 10 of these have neural functions. Differences detected in the array were validated with pyrosequencing. Ninety-five percent of the variance in DNAm in preterm infants was explained by 23 PCs; corticospinal tract shape associated with 6th PC, and gender and early nutritional exposure associated with the 7th PC. Preterm birth is associated with alterations in the methylome at sites that influence neural development and function. Differential methylation analysis has identified several promising candidate genes for understanding the genetic/epigenetic basis of preterm brain injury.
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Affiliation(s)
- S Sparrow
- MRC Centre for Reproductive Health, University of Edinburgh, Queen's Medical Research Institute, Edinburgh, UK
| | - J R Manning
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, UK
| | - J Cartier
- University/BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
| | - D Anblagan
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - M E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - C Piyasena
- University/BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
| | - R Pataky
- MRC Centre for Reproductive Health, University of Edinburgh, Queen's Medical Research Institute, Edinburgh, UK
| | - E J Moore
- MRC Centre for Reproductive Health, University of Edinburgh, Queen's Medical Research Institute, Edinburgh, UK
| | - S I Semple
- Clinical Research Imaging Centre, University of Edinburgh, Edinburgh, UK
| | | | - M Evans
- Department of Pathology, NHS Lothian, Edinburgh, UK
| | - A J Drake
- University/BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
| | - J P Boardman
- MRC Centre for Reproductive Health, University of Edinburgh, Queen's Medical Research Institute, Edinburgh, UK,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK,MRC Centre for Reproductive Health, University of Edinburgh, Queen's Medical Research Institute, 47 Little France Crescent, Room W1.26, Edinburgh EH16 4TJ, UK. E-mail:
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10
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Yeung ENW, Treskes P, Martin SF, Manning JR, Dunbar DR, Rogers SM, Le Bihan T, Lockman KA, Morley SD, Hayes PC, Nelson LJ, Plevris JN. Fibrinogen production is enhanced in an in-vitro model of non-alcoholic fatty liver disease: an isolated risk factor for cardiovascular events? Lipids Health Dis 2015; 14:86. [PMID: 26256740 PMCID: PMC4529985 DOI: 10.1186/s12944-015-0069-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2015] [Accepted: 06/29/2015] [Indexed: 12/25/2022] Open
Abstract
Background Cardiovascular disease (CVD) remains the major cause of excess mortality in patients with non-alcoholic fatty liver disease (NAFLD). The aim of this study was to investigate the individual contribution of NAFLD to CVD risk factors in the absence of pathogenic influences from other comorbidities often found in NAFLD patients, by using an established in-vitro model of hepatic steatosis. Methods Histopathological events in non-alcoholic fatty liver disease were recapitulated by focused metabolic nutrient overload of hepatoblastoma C3A cells, using oleate-treated-cells and untreated controls for comparison. Microarray and proteomic data from cell culture experiments were integrated into a custom-built systems biology database and proteogenomics analysis performed. Candidate genes with significant dysregulation and concomitant changes in protein abundance were identified and STRING association and enrichment analysis performed to identify putative pathogenic pathways. Results The search strategy yielded 3 candidate genes that were specifically and significantly up-regulated in nutrient-overloaded cells compared to untreated controls: fibrinogen alpha chain (2.2 fold), fibrinogen beta chain (2.3 fold) and fibrinogen gamma chain (2.1 fold) (all rank products pfp <0.05). Fibrinogen alpha and gamma chain also demonstrated significant concomitant increases in protein abundance (3.8-fold and 2.0-fold, respectively, p <0.05). Conclusions In-vitro modelling of NAFLD and reactive oxygen species formation in nutrient overloaded C3A cells, in the absence of pathogenic influences from other comorbidities, suggests that NAFLD is an isolated determinant of CVD. Nutrient overload-induced up-regulation of all three fibrinogen component subunits of the coagulation cascade provides a possible mechanism to explain the excess CVD mortality observed in NAFLD patients. Electronic supplementary material The online version of this article (doi:10.1186/s12944-015-0069-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Emily N W Yeung
- Hepatology Laboratory, Division of Health Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
| | - Philipp Treskes
- Hepatology Laboratory, Division of Health Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
| | - Sarah F Martin
- Kinetic Parameter Facility, SynthSys, Centre for Synthetic and Systems Biology, University of Edinburgh, C.H. Waddington Building, The Kings Buildings, Edinburgh, EH9 3JD, UK.
| | - Jonathan R Manning
- Bioinformatics Team, University/BHF Centre for Cardiovascular Science, University of Edinburgh, Queen's Medical Research Institute, 47 Little France Crescent, Edinburgh, EH16 4TJ, UK.
| | - Donald R Dunbar
- Bioinformatics Team, University/BHF Centre for Cardiovascular Science, University of Edinburgh, Queen's Medical Research Institute, 47 Little France Crescent, Edinburgh, EH16 4TJ, UK.
| | - Sophie M Rogers
- Kinetic Parameter Facility, SynthSys, Centre for Synthetic and Systems Biology, University of Edinburgh, C.H. Waddington Building, The Kings Buildings, Edinburgh, EH9 3JD, UK.
| | - Thierry Le Bihan
- Kinetic Parameter Facility, SynthSys, Centre for Synthetic and Systems Biology, University of Edinburgh, C.H. Waddington Building, The Kings Buildings, Edinburgh, EH9 3JD, UK.
| | - K Ann Lockman
- Hepatology Laboratory, Division of Health Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
| | - Steven D Morley
- Hepatology Laboratory, Division of Health Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
| | - Peter C Hayes
- Hepatology Laboratory, Division of Health Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
| | - Leonard J Nelson
- Hepatology Laboratory, Division of Health Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
| | - John N Plevris
- Hepatology Laboratory, Division of Health Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK.
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Conway BR, Betz B, Sheldrake TA, Manning JR, Dunbar DR, Dobyns A, Hughes J, Mullins JJ. Tight blood glycaemic and blood pressure control in experimental diabetic nephropathy reduces extracellular matrix production without regression of fibrosis. Nephrology (Carlton) 2015; 19:802-13. [PMID: 25196678 DOI: 10.1111/nep.12335] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/01/2014] [Indexed: 01/15/2023]
Abstract
AIMS Regression of albuminuria and renal fibrosis occurs in patients with diabetic nephropathy (DN) following tight control of blood glucose and blood pressure, however the pathways that promote regression remain poorly understood and we wished to characterize these using a rodent model. METHODS Diabetes was induced with streptozotocin in Cyp1a1mRen2 rats and hypertension was generated by inducing renin transgene expression with dietary indole-3-carbinol (I-3-C) for 28 weeks. At this point an 'injury cohort' was culled, while in a 'reversal cohort' glycaemia was tightly controlled using insulin implants and blood pressure normalized by withdrawing dietary I-3-C for a further 8 weeks. Pathways activated during and following reversal of diabetes and hypertension were assessed by microarray profiling. RESULTS Tight control of blood glucose and blood pressure reduced albuminuria and renal hypertrophy, but had no impact on renal fibrosis. 85 genes were up-regulated specifically during the injury phase, including genes encoding multiple myofibroblast and extracellular matrix (ECM) proteins. Conversely, 314 genes remained persistently elevated during reversal including genes linked to innate/adaptive immunity, phagocytosis, lysosomal processing and degradative metalloproteinases (MMPs). Despite increased MMP gene expression, MMP activity was suppressed during both injury and reversal, in association with up-regulation of tissue inhibitor of metalloproteinase-1 (TIMP-1) protein. Physical separation of the TIMP-1/MMP complexes during zymography of tissue homogenate restored MMP activity. CONCLUSION Normalization of blood glucose and pressure ameliorates albuminuria and inhibits excess ECM production, however persistent TIMP-1 expression hinders attempts at ECM remodelling. Therapies which counteract the action of TIMPs may accelerate scar resolution.
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Affiliation(s)
- Bryan R Conway
- Centre for Cardiovascular Science, British Heart Foundation/University of Edinburgh, Edinburgh, UK
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12
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Rabinovich RA, Drost E, Manning JR, Dunbar DR, Díaz-Ramos M, Lakhdar R, Bastos R, MacNee W. Genome-wide mRNA expression profiling in vastus lateralis of COPD patients with low and normal fat free mass index and healthy controls. Respir Res 2015; 16:1. [PMID: 25567521 PMCID: PMC4333166 DOI: 10.1186/s12931-014-0139-5] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2014] [Accepted: 10/24/2014] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Chronic Obstructive Pulmonary Disease (COPD) has significant systemic effects beyond the lungs amongst which muscle wasting is a prominent contributor to exercise limitation and an independent predictor of morbidity and mortality. The molecular mechanisms leading to skeletal muscle dysfunction/wasting are not fully understood and are likely to be multi-factorial. The need to develop therapeutic strategies aimed at improving skeletal muscle dysfunction/wasting requires a better understanding of the molecular mechanisms responsible for these abnormalities. Microarrays are powerful tools that allow the investigation of the expression of thousands of genes, virtually the whole genome, simultaneously. We aim at identifying genes and molecular pathways involved in skeletal muscle wasting in COPD. METHODS We assessed and compared the vastus lateralis transcriptome of COPD patients with low fat free mass index (FFMI) as a surrogate of muscle mass (COPDL) (FEV1 30 ± 3.6%pred, FFMI 15 ± 0.2 Kg.m(-2)) with patients with COPD and normal FFMI (COPDN) (FEV1 44 ± 5.8%pred, FFMI 19 ± 0.5 Kg.m(-2)) and a group of age and sex matched healthy controls (C) (FEV1 95 ± 3.9%pred, FFMI 20 ± 0.8 Kg.m(-2)) using Agilent Human Whole Genome 4x44K microarrays. The altered expression of several of these genes was confirmed by real time TaqMan PCR. Protein levels of P21 were assessed by immunoblotting. RESULTS A subset of 42 genes was differentially expressed in COPDL in comparison to both COPDN and C (PFP < 0.05; -1.5 ≥ FC ≥ 1.5). The altered expression of several of these genes was confirmed by real time TaqMan PCR and correlated with different functional and structural muscle parameters. Five of these genes (CDKN1A, GADD45A, PMP22, BEX2, CGREF1, CYR61), were associated with cell cycle arrest and growth regulation and had been previously identified in studies relating muscle wasting and ageing. Protein levels of CDKN1A, a recognized marker of premature ageing/cell cycle arrest, were also found to be increased in COPDL. CONCLUSIONS This study provides evidence of differentially expressed genes in peripheral muscle in COPD patients corresponding to relevant biological processes associated with skeletal muscle wasting and provides potential targets for future therapeutic interventions to prevent loss of muscle function and mass in COPD.
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Affiliation(s)
- Roberto A Rabinovich
- ELEGI Colt Laboratory, Centre for Inflammation Research, The Queen's Medical Research Institute, University of Edinburgh, 47 Little France Crescent, Edinburgh, Scotland, EH16 4TJ, UK.
| | - Ellen Drost
- ELEGI Colt Laboratory, Centre for Inflammation Research, The Queen's Medical Research Institute, University of Edinburgh, 47 Little France Crescent, Edinburgh, Scotland, EH16 4TJ, UK.
| | - Jonathan R Manning
- Centre for Cardiovascular Science, University of Edinburgh, Scotland, UK.
| | - Donald R Dunbar
- Centre for Cardiovascular Science, University of Edinburgh, Scotland, UK.
| | - MaCarmen Díaz-Ramos
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
| | - Ramzi Lakhdar
- ELEGI Colt Laboratory, Centre for Inflammation Research, The Queen's Medical Research Institute, University of Edinburgh, 47 Little France Crescent, Edinburgh, Scotland, EH16 4TJ, UK.
| | - Ricardo Bastos
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
- Ciber de Enfermedades Respiratorias (CIBERES), Barcelona, Spain.
| | - William MacNee
- ELEGI Colt Laboratory, Centre for Inflammation Research, The Queen's Medical Research Institute, University of Edinburgh, 47 Little France Crescent, Edinburgh, Scotland, EH16 4TJ, UK.
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Bellamy COC, Maxwell RS, Prost S, Azodo IA, Powell JJ, Manning JR. The value of immunophenotyping hepatocellular adenomas: consecutive resections at one UK centre. Histopathology 2012; 62:431-45. [DOI: 10.1111/his.12011] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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14
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Childs AJ, Kinnell HL, Manning JR, Dunbar DR, Anderson RA. Genome-Wide Transcriptomic Analysis Identifies SERPINE2, TGFBI and BASP1 as Novel Targets of Activin/TGF-Beta Signaling in the Human Fetal Ovary. Biol Reprod 2012. [DOI: 10.1093/biolreprod/87.s1.576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Conway BR, Rennie J, Bailey MA, Dunbar DR, Manning JR, Bellamy CO, Hughes J, Mullins JJ. Hyperglycemia and renin-dependent hypertension synergize to model diabetic nephropathy. J Am Soc Nephrol 2011; 23:405-11. [PMID: 22193383 DOI: 10.1681/asn.2011060577] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Rodent models exhibit only the earliest features of human diabetic nephropathy, which limits our ability to investigate new therapies. Hypertension is a prerequisite for advanced diabetic nephropathy in humans, so its rarity in typical rodent models may partly explain their resistance to nephropathy. Here, we used the Cyp1a1mRen2 rat, in which the murine renin-2 gene is incorporated under the Cytochrome P4501a1 promoter. In this transgenic strain, administration of low-dose dietary indole-3-carbinol induces moderate hypertension. In the absence of hypertension, streptozotocin-induced diabetes resulted in a 14-fold increase in albuminuria but only mild changes in histology and gene expression despite 28 weeks of marked hyperglycemia. In the presence of induced hypertension, hyperglycemia resulted in a 500-fold increase in albuminuria, marked glomerulosclerosis and tubulointerstitial fibrosis, and induction of many of the same pathways that are upregulated in the tubulointerstitium in human diabetic nephropathy. In conclusion, although induction of diabetes alone in rodents has limited utility to model human diabetic nephropathy, renin-dependent hypertension and hyperglycemia synergize to recapitulate many of the clinical, histological, and gene expression changes observed in humans.
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Affiliation(s)
- Bryan R Conway
- MRC Centre for Inflammation Research, University of Edinburgh, Edinburgh, Scotland, UK.
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Fox KAA, Carruthers KF, Dunbar DR, Graham C, Manning JR, De Raedt H, Buysschaert I, Lambrechts D, Van de Werf F. Underestimated and under-recognized: the late consequences of acute coronary syndrome (GRACE UK-Belgian Study). Eur Heart J 2010; 31:2755-64. [PMID: 20805110 DOI: 10.1093/eurheartj/ehq326] [Citation(s) in RCA: 308] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
AIM To define the long-term outcome of patients presenting with acute coronary syndrome [ST-segment elevation myocardial infarction (STEMI), and non-STEMI and unstable angina acute coronary syndrome (ACS) without biomarker elevation] and to test the hypothesis that the GRACE (Global Registry of Acute Coronary Events) risk score predicts mortality and death/MI at 5 years. METHODS AND RESULTS In the GRACE long-term study, UK and Belgian centres prospectively recruited and followed ACS patients for a median of 5 years (1797 days). Primary outcome events: deaths, cardiovascular deaths (CVDs) and MIs. Secondary events: stroke and re-hospitalization for ACS. There were 736 deaths, 19.8% (482 CVDs, 13%) and 347 (9.3%) MIs (>24 h), 261 strokes (7.7%), and 452 (17%) subsequent revascularizations. Rehospitalization was common: average 1.6 per patient; 31.2% had >1 admission, 9.2% had 5+ admissions. These events were despite high rates of guideline indicated therapies. The GRACE score was highly predictive of all-cause death, CVD, and CVD/MI at 5 years (death: χ(2) likelihood ratio 632; Wald 709.9, P< 0.0001, C-statistic 0.77; for CVD C-statistic 0.75, P < 0.0001; CVD/MI C-statistic 0.70, P < 0.0001). Compared with the low-risk GRACE stratum (ESC Guideline criteria), those with intermediate [hazard ratio (HR) 2.14, 95% CI 1.63, 2.81] and those with high-risk (HR 6.36, 95% CI 4.95, 8.16) had two- and six-fold higher risk of later death (Cox proportional hazard). A landmark analysis after 6 months confirmed that the GRACE score predicted long-term death (χ(2) likelihood ratio 265.4; Wald 289.5, P < 0.0001). Although in-hospital rates of death and MI are higher following STEMI, the cumulative rates of death (and CVD) were not different, by class of ACS, over the duration of follow-up (Wilcoxon = 1.5597, df = 1, P = 0.21). At 5 years after STEMI 269/1403 (19%) died; after non-STEMI 262/1170 (22%) after unstable angina (UA) 149/850 (17%). Two-thirds (68%) of STEMI deaths occurred after initial hospital discharge, but this was 86% for non-STEMI and 97% for UA. CONCLUSION The GRACE risk score predicts early and 5 year death and CVD/MI. Five year morbidity and mortality are as high in patients following non-ST MI and UA as seen following STEMI. Their morbidity burden is high (MI, stroke, readmissions) and the substantial late mortality in non-STE ACS is under-recognized. The findings highlight the importance of pursuing novel approaches to diminish long-term risk.
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Affiliation(s)
- Keith A A Fox
- Centre for Cardiovascular Science, University of Edinburgh, 49 Little France Crescent, Edinburgh EH16 4SB, UK.
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Manning JR, Bailey MA, Soares DC, Dunbar DR, Mullins JJ. In silico structure-function analysis of pathological variation in the HSD11B2 gene sequence. Physiol Genomics 2010; 42:319-30. [PMID: 20571110 DOI: 10.1152/physiolgenomics.00053.2010] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
11beta-Hydroxysteroid dehydrogenase type 2 (11betaHSD2) is a short-chain dehydrogenase/reductase (SDR) responsible for inactivating cortisol and preventing its binding to the mineralocorticoid receptor (MR). Nonfunctional mutations in HSD11B2, the gene encoding 11betaHSD2, cause the hypertensive syndrome of apparent mineralocorticoid excess (AME). Like other such Mendelian disorders, AME is rare but has nevertheless helped to illuminate principles fundamental to the regulation of blood pressure. Furthermore, polymorphisms in HSD11B2 have been associated with salt sensitivity, a major risk factor for cardiovascular mortality. It is therefore highly likely that sequence variation in HSD11B2, having subtle functional ramifications, will affect blood pressure in the wider population. In this study, a three-dimensional homology model of 11betaHSD2 was created and used to hypothesize the functional consequences in terms of protein structure of published mutations in HSD11B2. This approach underscored the strong genotype-phenotype correlation of AME: severe forms of the disease, associated with little in vivo enzyme activity, arise from mutations occurring in invariant alignment positions. These were predicted to exert gross structural changes in the protein. In contrast, those mutations causing a mild clinical phenotype were in less conserved regions of the protein that were predicted to be relatively more tolerant to substitution. Finally, a number of pathogenic mutations are shown to be associated with regions predicted to participate in dimer formation, and in protein stabilization, which may therefore suggest molecular mechanisms of disease.
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Affiliation(s)
- Jonathan R Manning
- Centre for Cardiovascular Science, Queen's Medical Research Institute, Western General Hospital, University of Edinburgh, Edinburgh, United Kingdom.
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Manning JR, Hedley A, Mullins JJ, Dunbar DR. Automated seeding of specialised wiki knowledgebases with BioKb. BMC Bioinformatics 2009; 10:291. [PMID: 19758431 PMCID: PMC2753848 DOI: 10.1186/1471-2105-10-291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2009] [Accepted: 09/16/2009] [Indexed: 12/03/2022] Open
Abstract
Background Wiki technology has become a ubiquitous mechanism for dissemination of information, and places strong emphasis on collaboration. We aimed to leverage wiki technology to allow small groups of researchers to collaborate around a specific domain, for example a biological pathway. Automatically gathered seed data could be modified by the group and enriched with domain specific information. Results We describe a software system, BioKb, implemented as a plugin for the TWiki engine, and designed to facilitate construction of a field-specific wiki containing collaborative and automatically generated content. Features of this system include: query of publicly available resources such as KEGG, iHOP and MeSH, to generate 'seed' content for topics; simple definition of structure for topics of different types via an administration page; and interactive incorporation of relevant PubMed references. An exemplar is shown for the use of this system, in the creation of the RAASWiki knowledgebase on the renin-angiotensin-aldosterone system (RAAS). RAASWiki has been seeded with data by use of BioKb, and will be the subject of ongoing development into an extensive knowledgebase on the RAAS. Conclusion The BioKb system is available from http://www.bioinf.mvm.ed.ac.uk/twiki/bin/view/TWiki/BioKbPlugin as a plugin for the TWiki engine.
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Manning JR, Jefferson ER, Barton GJ. The contrasting properties of conservation and correlated phylogeny in protein functional residue prediction. BMC Bioinformatics 2008; 9:51. [PMID: 18221517 PMCID: PMC2267696 DOI: 10.1186/1471-2105-9-51] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2007] [Accepted: 01/25/2008] [Indexed: 11/21/2022] Open
Abstract
Background Amino acids responsible for structure, core function or specificity may be inferred from multiple protein sequence alignments where a limited set of residue types are tolerated. The rise in available protein sequences continues to increase the power of techniques based on this principle. Results A new algorithm, SMERFS, for predicting protein functional sites from multiple sequences alignments was compared to 14 conservation measures and to the MINER algorithm. Validation was performed on an automatically generated dataset of 1457 families derived from the protein interactions database SNAPPI-DB, and a smaller manually curated set of 148 families. The best performing measure overall was Williamson property entropy, with ROC0.1 scores of 0.0087 and 0.0114 for domain and small molecule contact prediction, respectively. The Lancet method performed worse than random on protein-protein interaction site prediction (ROC0.1 score of 0.0008). The SMERFS algorithm gave similar accuracy to the phylogenetic tree-based MINER algorithm but was superior to Williamson in prediction of non-catalytic transient complex interfaces. SMERFS predicts sites that are significantly more solvent accessible compared to Williamson. Conclusion Williamson property entropy is the the best performing of 14 conservation measures examined. The difference in performance of SMERFS relative to Williamson in manually defined complexes was dependent on complex type. The best choice of analysis method is therefore dependent on the system of interest. Additional computation employed by Miner in calculation of phylogenetic trees did not produce improved results over SMERFS. SMERFS performance was improved by use of windows over alignment columns, illustrating the necessity of considering the local environment of positions when assessing their functional significance.
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Manning JR, Griesemer RA. Spontaneous lymphoma of the nonhuman primate. Lab Anim Sci 1974; 24:204-10. [PMID: 4360746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
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