liu.seSearch for publications in DiVA
Change search
Refine search result
1 - 11 of 11
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Alfirevic, Ana
    et al.
    University of Liverpool, UK.
    Gonzalez-Galarza, Faviel
    University of Liverpool, UK.
    Bell, Catherine
    University of Liverpool, UK.
    Martinsson, Klara
    University of Liverpool, UK.
    Platt, Vivien
    University of Liverpool, UK.
    Bretland, Giovanna
    University of Liverpool, UK.
    Evely, Jane
    University of Liverpool, UK.
    Lichtenfels, Maike
    University of Liverpool, UK.
    Cederbrant, Karin
    Safety Assessment, AstraZeneca, Gartuna, Södertälje, Sweden.
    French, Neil
    University of Liverpool, UK.
    Naisbitt, Dean
    University of Liverpool, UK.
    Park, B Kevin
    University of Liverpool, UK.
    Jones, Andrew R
    University of Liverpool, UK.
    Pirmohamed, Munir
    University of Liverpool, UK.
    In silico analysis of HLA associations with drug-induced liver injury: use of a HLA-genotyped DNA archive from healthy volunteers2012In: Genome Medicine, ISSN 1756-994X, E-ISSN 1756-994X, Vol. 4, no 6, article id 51Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Drug-induced liver injury (DILI) is one of the most common adverse reactions leading to product withdrawal post-marketing. Recently, genome-wide association studies have identified a number of human leukocyte antigen (HLA) alleles associated with DILI; however, the cellular and chemical mechanisms are not fully understood.

    METHODS: To study these mechanisms, we established an HLA-typed cell archive from 400 healthy volunteers. In addition, we utilized HLA genotype data from more than four million individuals from publicly accessible repositories such as the Allele Frequency Net Database, Major Histocompatibility Complex Database and Immune Epitope Database to study the HLA alleles associated with DILI. We utilized novel in silico strategies to examine HLA haplotype relationships among the alleles associated with DILI by using bioinformatics tools such as NetMHCpan, PyPop, GraphViz, PHYLIP and TreeView.

    RESULTS: We demonstrated that many of the alleles that have been associated with liver injury induced by structurally diverse drugs (flucloxacillin, co-amoxiclav, ximelagatran, lapatinib, lumiracoxib) reside on common HLA haplotypes, which were present in populations of diverse ethnicity.

    CONCLUSIONS: Our bioinformatic analysis indicates that there may be a connection between the different HLA alleles associated with DILI caused by therapeutically and structurally different drugs, possibly through peptide binding of one of the HLA alleles that defines the causal haplotype. Further functional work, together with next-generation sequencing techniques, will be needed to define the causal alleles associated with DILI.

  • 2.
    Auffray, Charles
    et al.
    European Institute Syst Biol and Med, France; University of Lyon, France.
    Balling, Rudi
    University of Luxembourg, Luxembourg.
    Barroso, Ines
    Wellcome Trust Sanger Institute, England.
    Bencze, Laszlo
    Semmelweis University, Hungary.
    Benson, Mikael
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Allergy Center.
    Bergeron, Jay
    Pfizer Inc, MA 02139 USA.
    Bernal-Delgado, Enrique
    IACS IIS Aragon, Spain.
    Blomberg, Niklas
    EL IXIR, England.
    Bock, Christoph
    Austrian Academic Science, Austria; Medical University of Vienna, Austria; Max Planck Institute Informat, Germany.
    Conesa, Ana
    Principe Felipe Research Centre, Spain; University of Florida, FL 32610 USA.
    Del Signore, Susanna
    Bluecompan Ltd, England.
    Delogne, Christophe
    KPMG Luxembourg, Luxembourg.
    Devilee, Peter
    Leiden University, Netherlands.
    Di Meglio, Alberto
    European Org Nucl Research CERN, Switzerland.
    Eijkemans, Marinus
    University of Utrecht, Netherlands.
    Flicek, Paul
    European Bioinformat Institute EMBL EBI, England.
    Graf, Norbert
    University of Saarland, Germany.
    Grimm, Vera
    Forschungszentrum Julich, Germany.
    Guchelaar, Henk-Jan
    Leiden University, Netherlands.
    Guo, Yi-Ke
    University of London Imperial Coll Science Technology and Med, England.
    Glynne Gut, Ivo
    BIST, Spain.
    Hanbury, Allan
    TU Wien, Austria.
    Hanif, Shahid
    Assoc British Pharmaceut Ind, England.
    Hilgers, Ralf-Dieter
    University of Klinikum Aachen, Germany.
    Honrado, Angel
    SYNAPSE Research Management Partners, Spain.
    Rod Hose, D.
    University of Sheffield, England.
    Houwing-Duistermaat, Jeanine
    University of Leeds, England.
    Hubbard, Tim
    Kings Coll London, England; Genom England, England.
    Helen Janacek, Sophie
    European Bioinformat Institute EMBL EBI, England.
    Karanikas, Haralampos
    University of Athens, Greece.
    Kievits, Tim
    Vitr Healthcare Holding BV, Netherlands.
    Kohler, Manfred
    Fraunhofer Institute Molecular Biol and Appl Ecol ScreeningPor, Germany.
    Kremer, Andreas
    ITTM SA, Luxembourg.
    Lanfear, Jerry
    Pfizer Ltd, England.
    Lengauer, Thomas
    Max Planck Institute for Informatics, Saarbrucken, Germany.
    Maes, Edith
    Health Econ and Outcomes Research, Belgium.
    Meert, Theo
    Janssen Pharmaceut NV, Belgium.
    Mueller, Werner
    University of Manchester, England.
    Nickel, Dorthe
    Institute Curie, France.
    Oledzki, Peter
    Linguamat Ltd, England.
    Pedersen, Bertrand
    PwC Luxembourg, Luxembourg.
    Petkovic, Milan
    Philips, Netherlands.
    Pliakos, Konstantinos
    KU Leuven Kulak, Belgium.
    Rattray, Magnus
    University of Manchester, England.
    Redon i Mas, Josep
    University of Valencia, Spain.
    Schneider, Reinhard
    University of Luxembourg, Luxembourg.
    Sengstag, Thierry
    SIB, Switzerland; University of Basel, Switzerland.
    Serra-Picamal, Xavier
    Agency Health Qual and Assessment Catalonia AQuAS, Spain.
    Spek, Wouter
    EuroBioForum Fdn, Netherlands.
    Vaas, Lea A. I.
    Fraunhofer Institute Molecular Biol and Appl Ecol ScreeningPor, Germany.
    van Batenburg, Okker
    EuroBioForum Fdn, Netherlands.
    Vandelaer, Marc
    Integrated BioBank Luxembourg, Luxembourg.
    Varnai, Peter
    Technopolis Grp, England.
    Villoslada, Pablo
    Hospital Clin Barcelona, Spain.
    Antonio Vizcaino, Juan
    European Bioinformat Institute EMBL EBI, England.
    Peter Mary Wubbe, John
    European Platform Patients Org Science and Ind Epposi, Belgium.
    Zanetti, Gianluigi
    CRS4, Italy; BBMRI ERIC, Austria.
    Making sense of big data in health research: Towards an EU action plan2016In: Genome Medicine, ISSN 1756-994X, E-ISSN 1756-994X, Vol. 8, no 71Article in journal (Refereed)
    Abstract [en]

    Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health arid healthcare for all Europearis.

  • 3.
    Auffray, Charles
    et al.
    European Institute Syst Biol and Med, France; University of Lyon, France.
    Balling, Rudi
    University of Luxembourg, Luxembourg.
    Barroso, Ines
    Wellcome Trust Sanger Institute, England.
    Bencze, Laszlo
    Semmelweis University, Hungary.
    Benson, Mikael
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Allergy Center.
    Bergeron, Jay
    Pfizer Inc, MA 02139 USA.
    Bernal-Delgado, Enrique
    IACS IIS Aragon, Spain.
    Blomberg, Niklas
    ELIXIR, England.
    Bock, Christoph
    Austrian Academic Science, Austria; Austrian Academic Science, Austria; Max Planck Institute Informat, Germany.
    Conesa, Ana
    Principe Felipe Research Centre, Spain; University of Florida, FL 32610 USA.
    Del Signore, Susanna
    Bluecompan Ltd, England.
    Delogne, Christophe
    KPMG Luxembourg, Luxembourg.
    Devilee, Peter
    Leiden University, Netherlands.
    Di Meglio, Alberto
    European Org Nucl Research, Switzerland.
    Eijkemans, Marinus
    University of Medical Centre Utrecht, Netherlands.
    Flicek, Paul
    EMBL EBI, England.
    Graf, Norbert
    University of Saarland, Germany.
    Grimm, Vera
    Forschungszentrum Julich, Germany.
    Guchelaar, Henk-Jan
    Leiden University, Netherlands.
    Guo, Yi-Ke
    Imperial Coll London, England.
    Glynne Gut, Ivo
    BIST, Spain.
    Hanbury, Allan
    TU Wien, Austria.
    Hanif, Shahid
    Assoc British Pharmaceut Ind, England.
    Hilgers, Ralf-Dieter
    Rhein Westfal TH Aachen, Germany.
    Honrado, Angel
    SYNAPSE Research Management Partners, Spain.
    Rod Hose, D.
    University of Sheffield, England.
    Houwing-Duistermaat, Jeanine
    University of Leeds, England.
    Hubbard, Tim
    Kings Coll London, England; Genom England, England.
    Helen Janacek, Sophie
    EMBL EBI, England.
    Karanikas, Haralampos
    University of Athens, Greece.
    Kievits, Tim
    Vitromics Healthcare Holding BV, Netherlands.
    Kohler, Manfred
    Fraunhofer Institute Molecular Biol and Appl Ecol ScreeningPor, Germany.
    Kremer, Andreas
    ITTM SA, Luxembourg.
    Lanfear, Jerry
    Pfizer Ltd, England.
    Lengauer, Thomas
    Max Planck Institute Informat, Germany.
    Maes, Edith
    Deloitte Belgium, Belgium.
    Meert, Theo
    Janssen Pharmaceut NV, Belgium.
    Muller, Werner
    University of Manchester, England.
    Nickel, Dothe
    Institute Curie, France.
    Oledzki, Peter
    Linguamat Ltd, England.
    Pedersen, Bertrand
    PwC Luxembourg, Luxembourg.
    Petkovic, Milan
    Philips, Netherlands.
    Pliakos, Konstantinos
    KU Leuven Kulak, Belgium.
    Rattray, Magnus
    University of Manchester, England.
    Redon i Mas, Josep
    University of Valencia, Spain.
    Schneider, Reinhard
    University of Luxembourg, Luxembourg.
    Sengstag, Thierry
    SIB, Switzerland; University of Basel, Switzerland.
    Serra-Picamal, Xavier
    Agency Health Qual and Assessment Catalonia AQuAS, Spain.
    Spek, Wouter
    EuroBioForum Fdn, Netherlands.
    Vaas, Lea A. I.
    Fraunhofer Institute Molecular Biol and Appl Ecol ScreeningPor, Germany.
    van Batenburg, Okker
    EuroBioForum Fdn, Netherlands.
    Vandelaer, Marc
    Integrated BioBank Luxembourg, Luxembourg.
    Varnai, Peter
    Technopolis Grp, England.
    Villoslada, Pablo
    Hospital Clin Barcelona, Spain.
    Antonio Vizcaino, Juan
    EMBL EBI, England.
    Peter Mary Wubbe, John
    Epposi, Belgium.
    Zanetti, Gianluigi
    CRS4, Italy; BBMRI ERIC, Austria.
    Correction: Making sense of big data in health research: towards an EU action plan (vol 8, pg 71, 2016)2016In: Genome Medicine, ISSN 1756-994X, E-ISSN 1756-994X, Vol. 8, article id 118Article in journal (Other academic)
    Abstract [en]

    n/a

  • 4.
    Björnsson, Bergthor
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Division of Surgery, Orthopedics and Oncology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Surgery in Linköping.
    Borrebaeck, Carl
    Lund Univ, Sweden.
    Elander, Nils
    Linköping University, Department of Clinical and Experimental Medicine, Division of Surgery, Orthopedics and Oncology. Linköping University, Faculty of Medicine and Health Sciences.
    Gasslander, Thomas
    Linköping University, Department of Clinical and Experimental Medicine, Division of Surgery, Orthopedics and Oncology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Surgery in Linköping.
    Gawel, Danuta
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences.
    Gustafsson, Mika
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Jornsten, Rebecka
    Univ Gothenburg, Sweden; Chalmers Univ Technol, Sweden.
    Jung Lee, Eun Jung
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences. Yonsei Univ, South Korea.
    Li, Xinxiu
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences.
    Lilja, Sandra
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences.
    Martinez, David
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Matussek, Andreas
    Karolinska Univ Hosp, Sweden; Dept Lab Med, Sweden.
    Sandström, Per
    Linköping University, Department of Clinical and Experimental Medicine, Division of Surgery, Orthopedics and Oncology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Surgery in Linköping.
    Schäfer, Samuel
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences.
    Stenmarker, Margaretha
    Futurum Acad Hlth and Care, Sweden; Inst Clin Sci, Sweden.
    Sun, Xiao-Feng
    Linköping University, Department of Clinical and Experimental Medicine, Division of Surgery, Orthopedics and Oncology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Oncology.
    Sysoev, Oleg
    Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Arts and Sciences.
    Zhang, Huan
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences.
    Benson, Mikael
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, H.K.H. Kronprinsessan Victorias barn- och ungdomssjukhus Linköping/Motala.
    Digital twins to personalize medicine2019In: Genome Medicine, ISSN 1756-994X, E-ISSN 1756-994X, Vol. 12, no 1, article id 4Article in journal (Refereed)
    Abstract [en]

    Personalized medicine requires the integration and processing of vast amounts of data. Here, we propose a solution to this challenge that is based on constructing Digital Twins. These are high-resolution models of individual patients that are computationally treated with thousands of drugs to find the drug that is optimal for the patient.

  • 5.
    Clermont, Gilles
    et al.
    University of Pittsburgh School of Medicine, PA , USA.
    Auffray, Charles
    CNRS Institute of Biological Sciences, Villejuif Cedex, France.
    Moreau, Yves
    K.U. Leuven, ESAT/SCD, Leuven-Heverlee, Belgium.
    Rocke, David M
    University of California, Davis, USA.
    Dalevi, Daniel
    Chalmers and Göteborg University, Sweden.
    Dubhashi, Devdatt
    Chalmers and Göteborg University, Sweden.
    Marshall, Dana R
    Meharry Medical College, Nashville, TN , USA.
    Raasch, Peter
    University of Rostock, Germany.
    Dehne, Frank
    Carleton University, Ottawa, Ontario, Canada.
    Provero, Paolo
    University of Torino, Italy .
    Tegner, Jesper
    Karolinska Universitetssjukhuset, Solna, Stockholm, Sweden.
    Aronow, Bruce J
    University of Cincinnati, OH, USA.
    Langston, Michael A
    University of Tennessee, Knoxville, USA.
    Benson, Mikael
    The Unit for Clinical Systems Biology, The Queen Silvia Children's Hospital, Gothenburg, Sweden.
    Bridging the gap between systems biology and medicine2009In: Genome Medicine, ISSN 1756-994X, E-ISSN 1756-994X, Vol. 1, no 9Article in journal (Refereed)
    Abstract [en]

    Systems biology has matured considerably as a discipline over the last decade, yet some of the key challenges separating current research efforts in systems biology and clinically useful results are only now becoming apparent. As these gaps are better defined, the new discipline of systems medicine is emerging as a translational extension of systems biology. How is systems medicine defined? What are relevant ontologies for systems medicine? What are the key theoretic and methodologic challenges facing computational disease modeling? How are inaccurate and incomplete data, and uncertain biologic knowledge best synthesized in useful computational models? Does network analysis provide clinically useful insight? We discuss the outstanding difficulties in translating a rapidly growing body of data into knowledge usable at the bedside. Although core-specific challenges are best met by specialized groups, it appears fundamental that such efforts should be guided by a roadmap for systems medicine drafted by a coalition of scientists from the clinical, experimental, computational, and theoretic domains.

  • 6.
    Gawel, Danuta
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences.
    Serra-Musach, Jordi
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences.
    Lilja, Sandra
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences.
    Aagesen, Jesper
    Reg Jonkoping Cty, Sweden.
    Arenas, Alex
    Univ Rovira and Virgili, Spain.
    Asking, Bengt
    Reg Jonkoping Cty, Sweden.
    Bengner, Malin
    Reg Jonkoping Cty, Sweden.
    Bjorkander, Janne
    Reg Jonkoping Cty, Sweden.
    Biggs, Sophie
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences.
    Ernerudh, Jan
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Clinical Immunology and Transfusion Medicine.
    Hjortswang, Henrik
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Gastroentorology.
    Karlsson, Jan-Erik
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Reg Jonkoping Cty, Sweden.
    Köpsén, Mattias
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Jung Lee, Eun Jung
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences. Yonsei Univ, South Korea.
    Lentini, Antonio
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences.
    Li, Xinxiu
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences.
    Magnusson, Mattias
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences.
    Martinez, David
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Matussek, Andreas
    Reg Jonkoping Cty, Sweden; Karolinska Inst, Sweden; Karolinska Univ Hosp, Sweden.
    Nestor, Colm
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences.
    Schafer, Samuel
    Linköping University, Department of Clinical and Experimental Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Seifert, Oliver
    Linköping University, Department of Clinical and Experimental Medicine, Division of Cell Biology. Linköping University, Faculty of Medicine and Health Sciences. Reg Jonkoping Cty, Sweden.
    Sonmez, Ceylan
    Linköping University, Department of Medical and Health Sciences, Division of Drug Research. Linköping University, Faculty of Medicine and Health Sciences.
    Stjernman, Henrik
    Reg Jonkoping Cty, Sweden.
    Tjärnberg, Andreas
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Wu, Simon
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Åkesson, Karin
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences. Reg Jonkoping Cty, Sweden.
    Shalek, Alex K.
    MIT, MA 02139 USA; Broad Inst MIT and Harvard, MA 02142 USA; Ragon Inst MGH MIT and Harvard, MA USA.
    Stenmarker, Margaretha
    Reg Jonkoping Cty, Sweden; Inst Clin Sci, Sweden.
    Zhang, Huan
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences.
    Gustafsson, Mika
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Benson, Mikael
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, H.K.H. Kronprinsessan Victorias barn- och ungdomssjukhus Linköping/Motala.
    A validated single-cell-based strategy to identify diagnostic and therapeutic targets in complex diseases2019In: Genome Medicine, ISSN 1756-994X, E-ISSN 1756-994X, Vol. 11, article id 47Article in journal (Refereed)
    Abstract [en]

    Background

    Genomic medicine has paved the way for identifying biomarkers and therapeutically actionable targets for complex diseases, but is complicated by the involvement of thousands of variably expressed genes across multiple cell types. Single-cell RNA-sequencing study (scRNA-seq) allows the characterization of such complex changes in whole organs.

    Methods

    The study is based on applying network tools to organize and analyze scRNA-seq data from a mouse model of arthritis and human rheumatoid arthritis, in order to find diagnostic biomarkers and therapeutic targets. Diagnostic validation studies were performed using expression profiling data and potential protein biomarkers from prospective clinical studies of 13 diseases. A candidate drug was examined by a treatment study of a mouse model of arthritis, using phenotypic, immunohistochemical, and cellular analyses as read-outs.

    Results

    We performed the first systematic analysis of pathways, potential biomarkers, and drug targets in scRNA-seq data from a complex disease, starting with inflamed joints and lymph nodes from a mouse model of arthritis. We found the involvement of hundreds of pathways, biomarkers, and drug targets that differed greatly between cell types. Analyses of scRNA-seq and GWAS data from human rheumatoid arthritis (RA) supported a similar dispersion of pathogenic mechanisms in different cell types. Thus, systems-level approaches to prioritize biomarkers and drugs are needed. Here, we present a prioritization strategy that is based on constructing network models of disease-associated cell types and interactions using scRNA-seq data from our mouse model of arthritis, as well as human RA, which we term multicellular disease models (MCDMs). We find that the network centrality of MCDM cell types correlates with the enrichment of genes harboring genetic variants associated with RA and thus could potentially be used to prioritize cell types and genes for diagnostics and therapeutics. We validated this hypothesis in a large-scale study of patients with 13 different autoimmune, allergic, infectious, malignant, endocrine, metabolic, and cardiovascular diseases, as well as a therapeutic study of the mouse arthritis model.

    Conclusions

    Overall, our results support that our strategy has the potential to help prioritize diagnostic and therapeutic targets in human disease.

  • 7.
    Gustafsson, Mika
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Health Sciences.
    Edström, Måns
    Linköping University, Department of Clinical and Experimental Medicine, Division of Inflammation Medicine. Linköping University, Faculty of Health Sciences.
    Gawel, Danuta
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Health Sciences.
    Nestor, Colm
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Health Sciences.
    Wang, Hui
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Health Sciences.
    Zhang, Huan
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Health Sciences.
    Barrenäs, Fredrik
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Health Sciences.
    Tojo, James
    Karolinska Institute, Sweden Centre Molecular Med, Sweden .
    Kockum, Ingrid
    Karolinska Institute, Sweden Centre Molecular Med, Sweden .
    Olsson, Tomas
    Karolinska Institute, Sweden Centre Molecular Med, Sweden .
    Serra-Musach, Jordi
    IDIBELL, Spain .
    Bonifaci, Nuria
    IDIBELL, Spain .
    Angel Pujana, Miguel
    IDIBELL, Spain .
    Ernerudh, Jan
    Linköping University, Department of Clinical and Experimental Medicine, Division of Inflammation Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Clinical Immunology and Transfusion Medicine.
    Benson, Mikael
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Allergy Center. Östergötlands Läns Landsting, Center of Paediatrics and Gynaecology and Obstetrics, Department of Paediatrics in Linköping.
    Integrated genomic and prospective clinical studies show the importance of modular pleiotropy for disease susceptibility, diagnosis and treatment2014In: Genome Medicine, ISSN 1756-994X, E-ISSN 1756-994X, Vol. 6, no 17Article in journal (Refereed)
    Abstract [en]

    Background: Translational research typically aims to identify and functionally validate individual, disease-specific genes. However, reaching this aim is complicated by the involvement of thousands of genes in common diseases, and that many of those genes are pleiotropic, that is, shared by several diseases. Methods: We integrated genomic meta-analyses with prospective clinical studies to systematically investigate the pathogenic, diagnostic and therapeutic roles of pleiotropic genes. In a novel approach, we first used pathway analysis of all published genome-wide association studies (GWAS) to find a cell type common to many diseases. Results: The analysis showed over-representation of the T helper cell differentiation pathway, which is expressed in T cells. This led us to focus on expression profiling of CD4(+) T cells from highly diverse inflammatory and malignant diseases. We found that pleiotropic genes were highly interconnected and formed a pleiotropic module, which was enriched for inflammatory, metabolic and proliferative pathways. The general relevance of this module was supported by highly significant enrichment of genetic variants identified by all GWAS and cancer studies, as well as known diagnostic and therapeutic targets. Prospective clinical studies of multiple sclerosis and allergy showed the importance of both pleiotropic and disease specific modules for clinical stratification. Conclusions: In summary, this translational genomics study identified a pleiotropic module, which has key pathogenic, diagnostic and therapeutic roles.

  • 8.
    Gustafsson, Mika
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Health Sciences.
    Nestor, Colm
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Health Sciences.
    Zhang, Huan
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Health Sciences.
    Barabasi, Albert-Laszlo
    Northeastern University, MA 02115 USA.
    Baranzini, Sergio
    University of Calif San Francisco, CA 94143 USA.
    Brunak, Soeren
    Technical University of Denmark, Denmark; University of Copenhagen, Denmark.
    Fan Chung, Kian
    University of London Imperial Coll Science Technology and Med, England.
    Federoff, Howard J.
    Georgetown University, DC 20057 USA.
    Gavin, Anne-Claude
    European Molecular Biol Lab, Germany.
    Meehan, Richard R.
    University of Edinburgh, Scotland.
    Picotti, Paola
    University of Zurich, Switzerland.
    Angel Pujana, Miguel
    Bellvitge Biomed Research Institute IDIBELL, Spain.
    Rajewsky, Nikolaus
    Max Delbruck Centre Molecular Med, Germany.
    Smith, Kenneth G. C.
    University of Cambridge, England; University of Cambridge, England.
    Sterk, Peter J.
    University of Amsterdam, Netherlands.
    Villoslada, Pablo
    Hospital Clin Barcelona, Spain; Hospital Clin Barcelona, Spain.
    Benson, Mikael
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Allergy Center. Östergötlands Läns Landsting, Center of Paediatrics and Gynaecology and Obstetrics, Department of Paediatrics in Linköping.
    Modules, networks and systems medicine for understanding disease and aiding diagnosis2014In: Genome Medicine, ISSN 1756-994X, E-ISSN 1756-994X, Vol. 6, no 82Article, review/survey (Refereed)
    Abstract [en]

    Many common diseases, such as asthma, diabetes or obesity, involve altered interactions between thousands of genes. High-throughput techniques (omics) allow identification of such genes and their products, but functional understanding is a formidable challenge. Network-based analyses of omics data have identified modules of disease-associated genes that have been used to obtain both a systems level and a molecular understanding of disease mechanisms. For example, in allergy a module was used to find a novel candidate gene that was validated by functional and clinical studies. Such analyses play important roles in systems medicine. This is an emerging discipline that aims to gain a translational understanding of the complex mechanisms underlying common diseases. In this review, we will explain and provide examples of how network-based analyses of omics data, in combination with functional and clinical studies, are aiding our understanding of disease, as well as helping to prioritize diagnostic markers or therapeutic candidate genes. Such analyses involve significant problems and limitations, which will be discussed. We also highlight the steps needed for clinical implementation.

  • 9.
    Merker, Matthias
    et al.
    German Ctr Infect Res DZIF, Germany; Res Ctr Borstel, Germany.
    Kohl, Thomas A.
    German Ctr Infect Res DZIF, Germany; Res Ctr Borstel, Germany.
    Barilar, Ivan
    German Ctr Infect Res DZIF, Germany; Res Ctr Borstel, Germany.
    Andres, Soenke
    Natl and WHO Supranat Reference Ctr Mycobacteria, Germany.
    Fowler, Philip W.
    Univ Oxford, England.
    Chryssanthou, Erja
    Karolinska Univ Hosp, Sweden; Karolinska Inst, Sweden.
    Angeby, Kristian
    Karolinska Inst, Sweden.
    Jureen, Pontus
    Publ Hlth Agcy Sweden, Sweden.
    Moradigaravand, Danesh
    Univ Birmingham, England.
    Parkhill, Julian
    Univ Cambridge, England.
    Peacock, Sharon J.
    Univ Cambridge, England.
    Schön, Thomas
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Inflammation and Infection. Linköping University, Faculty of Medicine and Health Sciences. Kalmar Cty Hosp, Sweden.
    Maurer, Florian P.
    Natl and WHO Supranat Reference Ctr Mycobacteria, Germany; Univ Med Ctr Hamburg Eppendorf, Germany.
    Walker, Timothy
    Univ Oxford, England.
    Koser, Claudio
    Univ Cambridge, England.
    Niemann, Stefan
    German Ctr Infect Res DZIF, Germany; Res Ctr Borstel, Germany.
    Phylogenetically informative mutations in genes implicated in antibiotic resistance in Mycobacterium tuberculosis complex2020In: Genome Medicine, ISSN 1756-994X, E-ISSN 1756-994X, Vol. 12, no 1, article id 27Article in journal (Refereed)
    Abstract [en]

    Background A comprehensive understanding of the pre-existing genetic variation in genes associated with antibiotic resistance in the Mycobacterium tuberculosis complex (MTBC) is needed to accurately interpret whole-genome sequencing data for genotypic drug susceptibility testing (DST). Methods We investigated mutations in 92 genes implicated in resistance to 21 anti-tuberculosis drugs using the genomes of 405 phylogenetically diverse MTBC strains. The role of phylogenetically informative mutations was assessed by routine phenotypic DST data for the first-line drugs isoniazid, rifampicin, ethambutol, and pyrazinamide from a separate collection of over 7000 clinical strains. Selected mutations/strains were further investigated by minimum inhibitory concentration (MIC) testing. Results Out of 547 phylogenetically informative mutations identified, 138 were classified as not correlating with resistance to first-line drugs. MIC testing did not reveal a discernible impact of a Rv1979c deletion shared by M. africanum lineage 5 strains on resistance to clofazimine. Finally, we found molecular evidence that some MTBC subgroups may be hyper-susceptible to bedaquiline and clofazimine by different loss-of-function mutations affecting a drug efflux pump subunit (MmpL5). Conclusions Our findings underline that the genetic diversity in MTBC has to be studied more systematically to inform the design of clinical trials and to define sound epidemiologic cut-off values (ECOFFs) for new and repurposed anti-tuberculosis drugs. In that regard, our comprehensive variant catalogue provides a solid basis for the interpretation of mutations in genotypic as well as in phenotypic DST assays.

  • 10.
    Serra-Musach, Jordi
    et al.
    Bellvitge Institute Biomed Research IDIBELL, Spain.
    Mateo, Francesca
    Bellvitge Institute Biomed Research IDIBELL, Spain.
    Capdevila-Busquets, Eva
    Barcelona Institute Science and Technology, Spain.
    Ruiz de Garibay, Gorka
    Bellvitge Institute Biomed Research IDIBELL, Spain.
    Zhang, Xiaohu
    NIH, MD 20850 USA.
    Guha, Raj
    NIH, MD 20850 USA.
    Thomas, Craig J.
    NIH, MD 20850 USA.
    Grueso, Judit
    VHIO, Spain.
    Villanueva, Alberto
    Bellvitge Institute Biomed Research IDIBELL, Spain.
    Jaeger, Samira
    Barcelona Institute Science and Technology, Spain.
    Heyn, Holger
    IDIBELL, Spain.
    Vizoso, Miguel
    IDIBELL, Spain.
    Perez, Hector
    IDIBELL, Spain.
    Cordero, Alex
    IDIBELL, Spain.
    Gonzalez-Suarez, Eva
    IDIBELL, Spain.
    Esteller, Manel
    IDIBELL, Spain; University of Barcelona, Spain; University of Barcelona, Spain; ICREA, Spain.
    Moreno-Bueno, Gema
    Autonomous University of Madrid, Spain; MD Anderson Int Fdn, Spain.
    Tjärnberg, Andreas
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Lazaro, Conxi
    IDIBELL, Spain.
    Serra, Violeta
    VHIO, Spain.
    Arribas, Joaquin
    ICREA, Spain; VHIO, Spain; Autonomous University of Barcelona, Spain.
    Benson, Mikael
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Allergy Center.
    Gustafsson, Mika
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Ferrer, Marc
    NIH, MD 20850 USA.
    Aloy, Patrick
    Barcelona Institute Science and Technology, Spain; ICREA, Spain.
    Angel Pujana, Miquel
    Bellvitge Institute Biomed Research IDIBELL, Spain.
    Cancer network activity associated with therapeutic response and synergism2016In: Genome Medicine, ISSN 1756-994X, E-ISSN 1756-994X, Vol. 8, no 88Article in journal (Refereed)
    Abstract [en]

    Background: Cancer patients often show no or only modest benefit from a given therapy. This major problem in oncology is generally attributed to the lack of specific predictive biomarkers, yet a global measure of cancer cell activity may support a comprehensive mechanistic understanding of therapy efficacy. We reasoned that network analysis of omic data could help to achieve this goal. Methods: A measure of "cancer network activity" (CNA) was implemented based on a previously defined network feature of communicability. The network nodes and edges corresponded to human proteins and experimentally identified interactions, respectively. The edges were weighted proportionally to the expression of the genes encoding for the corresponding proteins and relative to the number of direct interactors. The gene expression data corresponded to the basal conditions of 595 human cancer cell lines. Therapeutic responses corresponded to the impairment of cell viability measured by the half maximal inhibitory concentration (IC50) of 130 drugs approved or under clinical development. Gene ontology, signaling pathway, and transcription factor-binding annotations were taken from public repositories. Predicted synergies were assessed by determining the viability of four breast cancer cell lines and by applying two different analytical methods. Results: The effects of drug classes were associated with CNAs formed by different cell lines. CNAs also differentiate target families and effector pathways. Proteins that occupy a central position in the network largely contribute to CNA. Known key cancer-associated biological processes, signaling pathways, and master regulators also contribute to CNA. Moreover, the major cancer drivers frequently mediate CNA and therapeutic differences. Cell-based assays centered on these differences and using uncorrelated drug effects reveals novel synergistic combinations for the treatment of breast cancer dependent on PI3K-mTOR signaling. Conclusions: Cancer therapeutic responses can be predicted on the basis of a systems-level analysis of molecular interactions and gene expression. Fundamental cancer processes, pathways, and drivers contribute to this feature, which can also be exploited to predict precise synergistic drug combinations.

  • 11.
    Zhang, Huan
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, H.K.H. Kronprinsessan Victorias barn- och ungdomssjukhus.
    Klareskog, Lars
    Karolinska Inst, Sweden.
    Matussek, Andreas
    Karolinska Univ Hosp Lab, Sweden.
    Pfister, Stefan M.
    Hopp Childrens Canc Ctr Heidelberg KiTZ, Germany; German Canc Res Ctr, Germany; German Canc Consortium DKTK, Germany; Heidelberg Univ Hosp, Germany.
    Benson, Mikael
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, H.K.H. Kronprinsessan Victorias barn- och ungdomssjukhus.
    Editorial Material: Translating genomic medicine to the clinic: challenges and opportunities in GENOME MEDICINE, vol 11, issue , pp2019In: Genome Medicine, ISSN 1756-994X, E-ISSN 1756-994X, Vol. 11, article id 9Article in journal (Other academic)
    Abstract [en]

    Editorial summaryGenomic medicine has considerable potential to provide novel diagnostic and therapeutic solutions for patients who have molecularly complex diseases and who are not responding to existing therapies. To bridge the gap between genomic medicine and clinical practice, integration of various data types, resources, and joint international initiatives will be required.

1 - 11 of 11
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf