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

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...

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Autores principales: Koromani, Fjorda, Alonso, Nerea, Alves, Ines, Brandi, Maria Luisa, Foessl, Ines, Formosa, Melissa M., Morgenstern, Milana Frenkel, Karasik, David, Kolev, Mikhail, Makitie, Outi, Ntzani, Evangelia, Pietsch, Barbara Obermayer, Ohlsson, Claes, Rauner, Martina, Soe, Kent, Soldatovic, Ivan, Teti, Anna, Valjevac, Amina, Rivadeneira, Fernando
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8415473/
https://www.ncbi.nlm.nih.gov/pubmed/34484122
http://dx.doi.org/10.3389/fendo.2021.709815
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author Koromani, Fjorda
Alonso, Nerea
Alves, Ines
Brandi, Maria Luisa
Foessl, Ines
Formosa, Melissa M.
Morgenstern, Milana Frenkel
Karasik, David
Kolev, Mikhail
Makitie, Outi
Ntzani, Evangelia
Pietsch, Barbara Obermayer
Ohlsson, Claes
Rauner, Martina
Soe, Kent
Soldatovic, Ivan
Teti, Anna
Valjevac, Amina
Rivadeneira, Fernando
author_facet Koromani, Fjorda
Alonso, Nerea
Alves, Ines
Brandi, Maria Luisa
Foessl, Ines
Formosa, Melissa M.
Morgenstern, Milana Frenkel
Karasik, David
Kolev, Mikhail
Makitie, Outi
Ntzani, Evangelia
Pietsch, Barbara Obermayer
Ohlsson, Claes
Rauner, Martina
Soe, Kent
Soldatovic, Ivan
Teti, Anna
Valjevac, Amina
Rivadeneira, Fernando
author_sort Koromani, Fjorda
collection PubMed
description 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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spelling pubmed-84154732021-09-04 The “GEnomics of Musculo Skeletal Traits TranslatiOnal NEtwork”: Origins, Rationale, Organization, and Prospects Koromani, Fjorda Alonso, Nerea Alves, Ines Brandi, Maria Luisa Foessl, Ines Formosa, Melissa M. Morgenstern, Milana Frenkel Karasik, David Kolev, Mikhail Makitie, Outi Ntzani, Evangelia Pietsch, Barbara Obermayer Ohlsson, Claes Rauner, Martina Soe, Kent Soldatovic, Ivan Teti, Anna Valjevac, Amina Rivadeneira, Fernando Front Endocrinol (Lausanne) Endocrinology 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. Frontiers Media S.A. 2021-08-16 /pmc/articles/PMC8415473/ /pubmed/34484122 http://dx.doi.org/10.3389/fendo.2021.709815 Text en Copyright © 2021 Koromani, Alonso, Alves, Brandi, Foessl, Formosa, Morgenstern, Karasik, Kolev, Makitie, Ntzani, Pietsch, Ohlsson, Rauner, Soe, Soldatovic, Teti, Valjevac and Rivadeneira https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Endocrinology
Koromani, Fjorda
Alonso, Nerea
Alves, Ines
Brandi, Maria Luisa
Foessl, Ines
Formosa, Melissa M.
Morgenstern, Milana Frenkel
Karasik, David
Kolev, Mikhail
Makitie, Outi
Ntzani, Evangelia
Pietsch, Barbara Obermayer
Ohlsson, Claes
Rauner, Martina
Soe, Kent
Soldatovic, Ivan
Teti, Anna
Valjevac, Amina
Rivadeneira, Fernando
The “GEnomics of Musculo Skeletal Traits TranslatiOnal NEtwork”: Origins, Rationale, Organization, and Prospects
title The “GEnomics of Musculo Skeletal Traits TranslatiOnal NEtwork”: Origins, Rationale, Organization, and Prospects
title_full The “GEnomics of Musculo Skeletal Traits TranslatiOnal NEtwork”: Origins, Rationale, Organization, and Prospects
title_fullStr The “GEnomics of Musculo Skeletal Traits TranslatiOnal NEtwork”: Origins, Rationale, Organization, and Prospects
title_full_unstemmed The “GEnomics of Musculo Skeletal Traits TranslatiOnal NEtwork”: Origins, Rationale, Organization, and Prospects
title_short The “GEnomics of Musculo Skeletal Traits TranslatiOnal NEtwork”: Origins, Rationale, Organization, and Prospects
title_sort “genomics of musculo skeletal traits translational network”: origins, rationale, organization, and prospects
topic Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8415473/
https://www.ncbi.nlm.nih.gov/pubmed/34484122
http://dx.doi.org/10.3389/fendo.2021.709815
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