Identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration

Author:

Coutinho de Almeida Rodrigo1ORCID,Mahfouz Ahmed23,Mei Hailiang4,Houtman Evelyn1,den Hollander Wouter1,Soul Jamie5,Suchiman Eka1,Lakenberg Nico1,Meessen Jennifer16,Huetink Kasper6,Nelissen Rob G H H6,Ramos Yolande F M1,Reinders Marcel123,Meulenbelt Ingrid1

Affiliation:

1. Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands

2. Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands

3. Leiden Computational Biology Center, Leiden, The Netherlands

4. Sequence Analysis Support Core, Leiden University Medical Center, Leiden, The Netherlands

5. Skeletal Research Group, Institute of Genetic Medicine, Newcastle University, Central Parkway, Newcastle upon Tyne, UK

6. Department Orthopaedics, Leiden University Medical Center, Leiden, The Netherlands

Abstract

Abstract 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.

Funder

Foundation for Research in Rheumatology

Dutch Arthritis Society

BBMRI-NL complementation project

Ana Fonds

Dutch Scientific Research council NWO/ZonMW VICI scheme

Publisher

Oxford University Press (OUP)

Subject

Pharmacology (medical),Rheumatology

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