Mobasheri, A., Kapoor, M., Ali, S. A., Lang, A., & Madry, H. (2021). The future of deep phenotyping in osteoarthritis: How can high throughput omics technologies advance our understanding of the cellular and molecular taxonomy of the disease? Osteoarthritis and Cartilage Open, 3(4), 100144. https://doi.org/10.1016/j.ocarto.2021.100144
The future of deep phenotyping in osteoarthritis : how can high throughput omics technologies advance our understanding of the cellular and molecular taxonomy of the disease?
|Author:||Mobasheri, Ali1,2,3,4; Kapoor, Mohit5,6,7; Ali, Shabana Amanda8,9;|
1Research Unit of Medical Imaging, Physics and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland
2Department of Regenerative Medicine, State Research Institute Centre for Innovative Medicine, Vilnius, Lithuania
3Departments of Orthopedics, Rheumatology and Clinical Immunology, University Medical Center Utrecht, Utrecht, the Netherlands
4Department of Joint Surgery, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
5Schroeder Arthritis Institute, University Health Network, Toronto, ON, Canada
6Krembil Research Institute, University Health Network, Toronto, ON, Canada
7Department of Surgery and Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
8Bone and Joint Center, Henry Ford Health System, Detroit, MI, USA
9Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, USA
10Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Department of Rheumatology and Clinical Immunology, Berlin, Germany
11German Rheumatism Research Centre (DRFZ) Berlin, a Leibniz Institute, Berlin, Germany
12Center of Experimental Orthopaedics, Saarland University, Homburg, Germany
|Online Access:||PDF Full Text (PDF, 0.9 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2023080292927
|Publish Date:|| 2023-08-02
Osteoarthritis (OA) is the most common form of musculoskeletal disease with significant healthcare costs and unmet needs in terms of early diagnosis and treatment. Many of the drugs that have been developed to treat OA failed in phase 2 and phase 3 clinical trials or produced inconclusive and ambiguous results. High throughput omics technologies are a powerful tool to better understand the mechanisms of the development of OA and other arthritic diseases. In this paper we outline the strategic reasons for increasingly applying deep phenotyping in OA for the benefit of gaining a better understanding of disease mechanisms and developing targeted treatments. This editorial is intended to launch a special themed issue of Osteoarthritis and Cartilage Open addressing the timely topic of “Advances in omics technologies for deep phenotyping in osteoarthritis”. High throughput omics technologies are increasingly being applied in mechanistic studies of OA and other arthritic diseases. Applying multi-omics approaches in OA is a high priority and will allow us to gather new information on disease pathogenesis at the cellular level, and integrate data from diverse omics technology platforms to enable deep phenotyping. We anticipate that new knowledge in this area will allow us to harness the power of Big Data Analytics and resolve the extremely complex and overlapping clinical phenotypes into molecular endotypes, revealing new information about the cellular taxonomy of OA and “druggable pathways”, thus facilitating future drug development.
Osteoarthritis and cartilage open
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
3121 General medicine, internal medicine and other clinical medicine
Ali Mobasheri has received funding from the following sources: The European Commission Framework 7 programme (EU FP7; HEALTH.2012.2.4.5-2, project number 305815; Novel Diagnostics and Biomarkers for Early Identification of Chronic Inflammatory Joint Diseases). The Innovative Medicines Initiative Joint Undertaking under grant agreement No. 115770, resources of which are composed of financial contribution from the European Union’s Seventh Framework programme (FP7/2007-2013) and EFPIA companies’ in-kind contribution. Ali Mobasheri also acknowledges funding from the European Commission through a Marie Curie Intra-European Fellowship for Career Development grant (project number 625746; acronym: CHONDRION; FP7-PEOPLE-2013-IEF) and financial support from the European Structural and Social Funds (ES Struktūrinės Paramos) through the Research Council of Lithuania (Lietuvos Mokslo Taryba) according to the activity “Improvement of researchers’ qualification by implementing world-class R&D projects” of Measure No. 09.3.3-LMT-K-712 (grant application code: 09.3.3-LMT-K-712-01-0157, agreement No. DOTSUT-215) and the new funding programme: “Attracting Foreign Researchers for Research Implementation (2018-2022)”, Grant No 01.2.2-LMT-K-718-02-0022.
© 2021 The Authors. Published by Elsevier Ltd on behalf of Osteoarthritis Research Society International (OARSI). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).