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Identification of a differential metabolite-based signature in patients with late-stage knee osteoarthritis.
- Source :
-
Osteoarthritis and cartilage open [Osteoarthr Cartil Open] 2022 Apr 02; Vol. 4 (3), pp. 100258. Date of Electronic Publication: 2022 Apr 02 (Print Publication: 2022). - Publication Year :
- 2022
-
Abstract
- Objective: Multiple disease phenotypes have been identified in knee osteoarthritis (OA) patients based on anthropometric, sociodemographic and clinical factors; however, differential systemic metabolite-based signatures in OA patients are not well understood. We sought to identify differential plasma metabolome signatures in a cross-sectional sample of late-stage knee OA patients.<br />Methods: Plasma from 214 (56.5% female; mean age = 67.58 years) non-diabetic, non-obese (BMI <30 kg/m <superscript>2</superscript> , mean = 26.25 kg/m <superscript>2</superscript> ), radiographic KL 3/4 primary knee OA patients was analyzed by metabolomics. Patients with post-traumatic OA and rheumatoid arthritis were excluded. Hierarchical clustering was used to identify patient clusters based on metabolite levels. A refined metabolite signature differentiating patient clusters was determined based on ≥ 10% difference, significance by FDR-adjusted t -test (q-value < 0.05), and random forests importance score ≥1, and analyzed by AUROC. Bioinformatics analysis was used to identify genes linked to ≥2 annotated metabolites. Associated enriched pathways (q < 0.05) were determined.<br />Results: Two patient clusters were determined based on the levels of 151 metabolites identified. Metabolite signature refinement found 24 metabolites could accurately predict cluster classification within the sample (AUC = 0.921). Fifty-six genes were linked to at least 2 KEGG annotated metabolites. Pathway analysis found 26/56 genes were linked to enriched pathways including tRNA acylation and B-vitamin metabolism.<br />Conclusion: This study demonstrates systemic metabolites can classify a cross-sectional cohort of OA patients into distinct clusters. Links between metabolites, genes and pathways can help determine biological differences between OA patients, potentially improving precision medicine and decision-making.<br />Competing Interests: The authors declare no conflicts of interest related to this manuscript.<br /> (© 2022 Published by Elsevier Ltd on behalf of Osteoarthritis Research Society International (OARSI).)
Details
- Language :
- English
- ISSN :
- 2665-9131
- Volume :
- 4
- Issue :
- 3
- Database :
- MEDLINE
- Journal :
- Osteoarthritis and cartilage open
- Publication Type :
- Academic Journal
- Accession number :
- 36474953
- Full Text :
- https://doi.org/10.1016/j.ocarto.2022.100258