The “GEnomics of Musculo Skeletal Traits TranslatiOnal NEtwork”: Origins, Rationale, Organization, and Prospects

Koromani F et al., Front. Endocrinol., 16 August 2021

Review article  https://doi.org/10.3389/fendo.2021.709815

Fjorda Koromani^1,2,3, Nerea Alonso⁴, Ines Alves⁵, Maria Luisa Brandi⁶, Ines Foessl⁷, Melissa M. Formosa⁸, Milana Frenkel Morgenstern⁹, David Karasik⁹, Mikhail Kolev¹⁰, Outi Makitie^11,12,13, Evangelia Ntzani^14,15, Barbara Obermayer Pietsch⁷, Claes Ohlsson¹⁶, Martina Rauner¹⁷, Kent Soe^18,19,20, Ivan Soldatovic²¹, Anna Teti²², Amina Valjevac²³ and Fernando Rivadeneira^1*

• ¹Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, Netherlands
• ²Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
• ³Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, Netherlands
• ⁴Rheumatology and Bone Disease Unit, CGEM-IGMM, University of Edinburgh, Edinburgh, United Kingdom
• ⁵ANDO Portugal, Évora, Portugal
• ⁶Department of Surgery and Translational Medicine (M.L.B.), University of Florence, Florence, Italy
• ⁷Department of Internal Medicine, Division of Endocrinology and Diabetology, Endocrinology Lab Platform, Medical University Graz, Graz, Austria
• ⁸Department of Applied Biomedical Science, Faculty of Health Sciences, University of Malta, Msida, Malta
• ⁹Azrieli Faculty of Medicine, Bar-Ilan University, Ramat Gan, Israel
• ¹⁰Department of Mathematics, South-West University Neofit Rilski, Blagoevgrad, Bulgaria
• ¹¹Children’s Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
• ¹²Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
• ¹³Folkhälsan Research Center, Folkhälsan Institute of Genetics, Helsinki, Finland
• ¹⁴Department of Hygiene and Epidemiology, Medical School, University of Ioannina, Ioannina, Greece
• ¹⁵Department of Health Services, Policy and Practice, Center for Research Synthesis in Health, School of Public Health, Brown University, Providence, RI, United States
• ¹⁶Centre for Bone and Arthritis Research, Institute of Medicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
• ¹⁷Department of Medicine III, Medical Faculty, Technische Universität Dresden, Dresden, Germany
• ¹⁸Clinical Cell Biology, Department of Pathology, Odense University Hospital, Odense, Denmark
• ¹⁹Clinical Cell Biology, Pathology Research Unit, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
• ²⁰Department of Molecular Medicine, University of Southern Denmark, Odense, Denmark
• ²¹Institute of Biostatistics, University of Belgrade, Belgrade, Serbia
• ²²Department of Biotechnological and Applied Clinical Sciences, L’Aquila, Italy
• ²³Department of Physiology, Medical Faculty University of Sarajevo, Sarajevo, Bosnia and Herzegovina

Introduction

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 The European Cooperation in Science and Technology (COST). GEMSTONE includes six working groups (WG), each with specific objectives: WG1-Study populations and expertise groups: 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-Phenotyping: describe ways to decompose the phenotypes of the different functional studies into meaningful components that will aid the interpretation of identified biological pathways. WG3 Monogenic conditions – human KO models: 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 Functional investigations: creating a roadmap of genes and pathways to be prioritized for functional assessment in cell and organism models of the musculoskeletal system. WG5 Bioinformatics seeks the integration of the knowledge derived from the distinct efforts, with particular emphasis on systems biology and artificial intelligence applications. Finally, WG6 Translational outreach: 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.

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