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Identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration
OBJECTIVE: To identify OA subtypes based on cartilage transcriptomic data in cartilage tissue and characterize their underlying pathophysiological processes and/or clinically relevant characteristics. METHODS: This study includes n = 66 primary OA patients (41 knees and 25 hips), who underwent a joi...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7937023/ https://www.ncbi.nlm.nih.gov/pubmed/32885253 http://dx.doi.org/10.1093/rheumatology/keaa391 |
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author | Coutinho de Almeida, Rodrigo Mahfouz, Ahmed Mei, Hailiang Houtman, Evelyn den Hollander, Wouter Soul, Jamie Suchiman, Eka Lakenberg, Nico Meessen, Jennifer Huetink, Kasper Nelissen, Rob G H H Ramos, Yolande F M Reinders, Marcel Meulenbelt, Ingrid |
author_facet | Coutinho de Almeida, Rodrigo Mahfouz, Ahmed Mei, Hailiang Houtman, Evelyn den Hollander, Wouter Soul, Jamie Suchiman, Eka Lakenberg, Nico Meessen, Jennifer Huetink, Kasper Nelissen, Rob G H H Ramos, Yolande F M Reinders, Marcel Meulenbelt, Ingrid |
author_sort | Coutinho de Almeida, Rodrigo |
collection | PubMed |
description | OBJECTIVE: To identify OA subtypes based on cartilage transcriptomic data in cartilage tissue and characterize their underlying pathophysiological processes and/or clinically relevant characteristics. METHODS: This study includes n = 66 primary OA patients (41 knees and 25 hips), who underwent a joint replacement surgery, from which macroscopically unaffected (preserved, n = 56) and lesioned (n = 45) OA articular cartilage were collected [Research Arthritis and Articular Cartilage (RAAK) study]. Unsupervised hierarchical clustering analysis on preserved cartilage transcriptome followed by clinical data integration was performed. Protein–protein interaction (PPI) followed by pathway enrichment analysis were done for genes significant differentially expressed between subgroups with interactions in the PPI network. RESULTS: Analysis of preserved samples (n = 56) resulted in two OA subtypes with n = 41 (cluster A) and n = 15 (cluster B) patients. The transcriptomic profile of cluster B cartilage, relative to cluster A (DE-AB genes) showed among others a pronounced upregulation of multiple genes involved in chemokine pathways. Nevertheless, upon investigating the OA pathophysiology in cluster B patients as reflected by differentially expressed genes between preserved and lesioned OA cartilage (DE-OA-B genes), the chemokine genes were significantly downregulated with OA pathophysiology. Upon integrating radiographic OA data, we showed that the OA phenotype among cluster B patients, relative to cluster A, may be characterized by higher joint space narrowing (JSN) scores and low osteophyte (OP) scores. CONCLUSION: Based on whole-transcriptome profiling, we identified two robust OA subtypes characterized by unique OA, pathophysiological processes in cartilage as well as a clinical phenotype. We advocate that further characterization, confirmation and clinical data integration is a prerequisite to allow for development of treatments towards personalized care with concurrently more effective treatment response. |
format | Online Article Text |
id | pubmed-7937023 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-79370232021-03-10 Identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration Coutinho de Almeida, Rodrigo Mahfouz, Ahmed Mei, Hailiang Houtman, Evelyn den Hollander, Wouter Soul, Jamie Suchiman, Eka Lakenberg, Nico Meessen, Jennifer Huetink, Kasper Nelissen, Rob G H H Ramos, Yolande F M Reinders, Marcel Meulenbelt, Ingrid Rheumatology (Oxford) Clinical Science OBJECTIVE: To identify OA subtypes based on cartilage transcriptomic data in cartilage tissue and characterize their underlying pathophysiological processes and/or clinically relevant characteristics. METHODS: This study includes n = 66 primary OA patients (41 knees and 25 hips), who underwent a joint replacement surgery, from which macroscopically unaffected (preserved, n = 56) and lesioned (n = 45) OA articular cartilage were collected [Research Arthritis and Articular Cartilage (RAAK) study]. Unsupervised hierarchical clustering analysis on preserved cartilage transcriptome followed by clinical data integration was performed. Protein–protein interaction (PPI) followed by pathway enrichment analysis were done for genes significant differentially expressed between subgroups with interactions in the PPI network. RESULTS: Analysis of preserved samples (n = 56) resulted in two OA subtypes with n = 41 (cluster A) and n = 15 (cluster B) patients. The transcriptomic profile of cluster B cartilage, relative to cluster A (DE-AB genes) showed among others a pronounced upregulation of multiple genes involved in chemokine pathways. Nevertheless, upon investigating the OA pathophysiology in cluster B patients as reflected by differentially expressed genes between preserved and lesioned OA cartilage (DE-OA-B genes), the chemokine genes were significantly downregulated with OA pathophysiology. Upon integrating radiographic OA data, we showed that the OA phenotype among cluster B patients, relative to cluster A, may be characterized by higher joint space narrowing (JSN) scores and low osteophyte (OP) scores. CONCLUSION: Based on whole-transcriptome profiling, we identified two robust OA subtypes characterized by unique OA, pathophysiological processes in cartilage as well as a clinical phenotype. We advocate that further characterization, confirmation and clinical data integration is a prerequisite to allow for development of treatments towards personalized care with concurrently more effective treatment response. Oxford University Press 2020-09-04 /pmc/articles/PMC7937023/ /pubmed/32885253 http://dx.doi.org/10.1093/rheumatology/keaa391 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of the British Society for Rheumatology. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Clinical Science Coutinho de Almeida, Rodrigo Mahfouz, Ahmed Mei, Hailiang Houtman, Evelyn den Hollander, Wouter Soul, Jamie Suchiman, Eka Lakenberg, Nico Meessen, Jennifer Huetink, Kasper Nelissen, Rob G H H Ramos, Yolande F M Reinders, Marcel Meulenbelt, Ingrid Identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration |
title | Identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration |
title_full | Identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration |
title_fullStr | Identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration |
title_full_unstemmed | Identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration |
title_short | Identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration |
title_sort | identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration |
topic | Clinical Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7937023/ https://www.ncbi.nlm.nih.gov/pubmed/32885253 http://dx.doi.org/10.1093/rheumatology/keaa391 |
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