The "GEnomics of Musculo Skeletal Traits TranslatiOnal NEtwork": Origins, Rationale, Organization, and Prospects.

Journal: Frontiers in endocrinology
PMID:

Abstract

Musculoskeletal research has been enriched in the past ten years with a great wealth of new discoveries arising from genome wide association studies (GWAS). In addition to the novel factors identified by GWAS, the advent of whole-genome and whole-exome sequencing efforts in family based studies has also identified new genes and pathways. However, the function and the mechanisms by which such genes influence clinical traits remain largely unknown. There is imperative need to bring multidisciplinary expertise together that will allow translating these genomic discoveries into useful clinical applications with the potential of improving patient care. Therefore "GEnomics of MusculoSkeletal traits TranslatiOnal NEtwork" (GEMSTONE) aims to set the ground for the: 1) functional characterization of discovered genes and pathways; 2) understanding of the correspondence between molecular and clinical assessments; and 3) implementation of novel methodological approaches. This research network is funded by (COST). GEMSTONE includes six working groups (WG), each with specific objectives: WG1- creating, maintaining and updating an inventory of experts and resources (studies and datasets) participating in the network, helping to assemble focus groups defined by phenotype, functional and methodological expertise. WG2- describe ways to decompose the phenotypes of the different functional studies into meaningful components that will aid the interpretation of identified biological pathways. WG3 makes an inventory of genes underlying musculoskeletal monogenic conditions that aids the assignment of genes to GWAS signals and prioritizing GWAS genes as candidates responsible for monogenic presentations, through biological plausibility. WG4 : creating a roadmap of genes and pathways to be prioritized for functional assessment in cell and organism models of the musculoskeletal system. WG5 seeks the integration of the knowledge derived from the distinct efforts, with particular emphasis on systems biology and artificial intelligence applications. Finally, WG6 : makes a synopsis of the knowledge derived from the distinct efforts, allowing to prioritize factors within biological pathways, use refined disease trait definitions and/or improve study design of future investigations in a potential therapeutic context (e.g. clinical trials) for musculoskeletal diseases.

Authors

  • Fjorda Koromani
    Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, Netherlands.
  • Nerea Alonso
    Department of Organic Chemistry, USC, 15782 Santiago de Compostela, Spain.
  • Ines Alves
    ANDO Portugal, Évora, Portugal.
  • Maria Luisa Brandi
    Department of Surgery and Translational Medicine (M.L.B.), University of Florence, Florence, Italy.
  • Ines Foessl
    Department of Internal Medicine, Division of Endocrinology and Diabetology, Endocrinology Lab Platform, Medical University Graz, Graz, Austria.
  • Melissa M Formosa
    Department of Applied Biomedical Science, Faculty of Health Sciences, University of Malta, Msida, Malta.
  • Milana Frenkel Morgenstern
    Azrieli Faculty of Medicine, Bar-Ilan University, Ramat Gan, Israel.
  • David Karasik
    Azrieli Faculty of Medicine, Bar-Ilan University, Ramat Gan, Israel.
  • Mikhail Kolev
    Department of Mathematics, South-West University Neofit Rilski, Blagoevgrad, Bulgaria.
  • Outi Makitie
    Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
  • Evangelia Ntzani
    Department of Hygiene and Epidemiology, Medical School, University of Ioannina, Ioannina, Greece.
  • Barbara Obermayer Pietsch
    Department of Internal Medicine, Division of Endocrinology and Diabetology, Endocrinology Lab Platform, Medical University Graz, Graz, Austria.
  • Claes Ohlsson
    Centre for Bone and Arthritis Research, Institute of Medicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden.
  • Martina Rauner
    Department of Medicine III, Medical Faculty, Technische Universität Dresden, Dresden, Germany.
  • Kent Soe
    Clinical Cell Biology, Department of Pathology, Odense University Hospital, Odense, Denmark.
  • Ivan Soldatovic
    Institute of Biostatistics, University of Belgrade, Belgrade, Serbia.
  • Anna Teti
    Department of Biotechnological and Applied Clinical Sciences, L'Aquila, Italy.
  • Amina Valjevac
    Department of Physiology, Medical Faculty University of Sarajevo, Sarajevo, Bosnia and Herzegovina.
  • Fernando Rivadeneira
    Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, Netherlands.