A review of applications of metabolomics in osteoarthritis

Li, Jie-Ting; Zeng, Ni; Yan, Zhi-Peng; Liao, Tao; Ni, Guo‐Xin

doi:10.1007/s10067-020-05511-8

Cited by 30 publications

(17 citation statements)

References 82 publications

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“…Arginine has anti-inflammatory and antioxidant properties and is a prerequisite for the syncretization of many molecules [ 26 ]. Arginine can contribute to inflammation-related diseases including osteoarthritis [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

Analysis of Serum Metabolomics in Rats with Osteoarthritis by Mass Spectrometry

et al. 2021

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Osteoarthritis is a common multifactorial chronic disease that occurs in articular cartilage, subchondral bone, and periarticular tissue. The pathogenesis of OA is still unclear. To investigate the differences in serum metabolites between OA and the control group, liquid chromatography/mass spectrometry (LC/MS)-based metabolomics was used. To reveal the pathogenesis of OA, 12 SD male rats were randomly divided into control and OA groups using collagenase to induce OA for modeling, and serum was collected 7 days after modeling for testing. The OA group was distinguished from the control group by principal component analysis and orthogonal partial least squares-discriminant analysis, and six biomarkers were finally identified. These biomarkers were metabolized through tryptophan metabolism, glutamate metabolism, nitrogen metabolism, spermidine metabolism, and fatty acid metabolism pathways. The study identified metabolites that may be altered in OA, suggesting a role in OA through relevant metabolic pathways. Metabolomics, as an important tool for studying disease mechanisms, provides useful information for studying the metabolic mechanisms of OA.

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Section: Discussionmentioning

confidence: 99%

Analysis of Serum Metabolomics in Rats with Osteoarthritis by Mass Spectrometry

et al. 2021

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“…By using an untargeted approach, metabolomics encompasses the study of the most abundant small molecules (metabolites) in whole organisms, tissues, cells, biofluids, and culture media to better understand the metabolic changes occurring during physiological and pathological conditions [21][22][23] . This technique can be applied in a…”

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confidence: 99%

1H-NMR metabolomic profile of healthy and osteoarthritic canine synovial fluid before and after UC-II supplementation

Stabile

Girelli

Lacitignola

et al. 2022

Sci Rep

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The aim of the study was to compare the metabolomic synovial fluid (SF) profile of dogs affected by spontaneous osteoarthritis (OA) and supplemented with undenatured type II collagen (UC-II), with that of healthy control dogs. Client-owned dogs were enrolled in the study and randomized in two different groups, based on the presence/absence of OA (OA group and OA-free group). All dogs were clinically evaluated and underwent SF sampling for 1H-Nuclear Magnetic Resonance spectroscopy (1H-NMR) analysis at time of presentation. All dogs included in OA group were supplemented with UC-II orally administered for 30 days. After this period, they were reassessed (OA-T30). The differences in the 1H-NMR metabolic SFs profiles between groups (OA-free, OA-T0 and OA-T30) were studied. The multivariate statistical analysis performed on SFs under different conditions (OA-T0 vs OA-T30 SFs; OA-T0 vs OA-free SFs and OA-T30 vs OA-free SFs) gave models with excellent goodness of fit and predictive parameters, revealed by a marked separation between groups. β-Hydroxybutyrate was identified as a characteristic compound of osteoarthritic joints, showing the important role of fat metabolism during OA. The absence of β-hydroxybutyrate after UC-II supplementation suggests the supplement’s effectiveness in rebalancing the metabolism inside the joint. The unexpectedly high level of lactate in the OA-free group suggests that lactate could not be considered a good marker for OA. These results prove that 1H-NMR-based metabolomic analysis is a valid tool to study and monitor OA and that UC-II improves clinical symptoms and the SF metabolic profile in OA dogs.

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“…Based on the above information analysis, in the initial stage of ONFH, reduced angiogenesis, insu cient blood supply, hypoxia, metabolic disorders, leading to local osteonecrosis, apoptosis, osteoclastmediated bone resorption [20,32,33] . Then the osteoblast-mediated repair response begins [34,35] .…”

Section: Discussionmentioning

confidence: 99%

Analysis of Differentially Expressed Genes in Osteonecrosis of Femoral Head, Osteoarthritis, and Rheumatoid Arthritis by Integrated Microarray Analysis

Zhao¹,

liu²,

li³

et al. 2021

Preprint

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BackgroundOsteonecrosis of femoral head (ONFH), osteoarthritis (OA) and rheumatoid arthritis (RA) are common diseases of hip joint, which will damage the joint to varying degrees, and will affect the mobility and quality of life of patients in severe cases. A better understanding of the expression of articular cartilage degeneration genes seems to be very important for further understanding the molecular mechanism of the joint action of the three diseases.Objectivethe purpose of this study was to explore the pathogenesis of cartilage injury in three diseases by analyzing the data sets of multiple gene expression groups and synthesizing the differentially expressed genes (DEGs) of ONFH, OA and RA.Methodsthe gene expression datasets of ONFH, OA and RA were obtained from Gene Expression Omnibus. Through the comprehensive analysis of multiple gene expression data sets, the common differentially expressed genes and specific DEGs in these diseases were found. Gene ontology (GO) analysis, KEGG pathway and protein-protein interaction analysis were used to investigate the functions of the altered proteins and biological pathways.ResultsA total of 59 common differentially expressed genes were obtained by GSE74089 and GSE55235 data sets, including 44 up-regulated genes and 15 down-regulated genes. GO and KEGG pathway enrichment analysis showed that DEGs concentrated on extracellular structure organization, extracellular matrix organization, fibrillar collagen trimer, platelet-derived growth factor binding, Relaxin signaling pathway, Protein digestion and absorption. Some hub genes with high interactions such as COL1A2, MMP1, VEGFC, SPP1, etc. Independent GEO dataset verification results show that these genes are consistent with the experimental results.ConclusionIn this study, bioinformatics methods were used to identify the common differential genes of ONFH, OA and RA, and to analyze the occurrence and development of cartilage degeneration or osteogenic diseases induced by them. To provide molecular basis for follow-up experiments and clinical efficacy.

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A review of applications of metabolomics in osteoarthritis

Cited by 30 publications

References 82 publications

Analysis of Serum Metabolomics in Rats with Osteoarthritis by Mass Spectrometry

Analysis of Serum Metabolomics in Rats with Osteoarthritis by Mass Spectrometry

1H-NMR metabolomic profile of healthy and osteoarthritic canine synovial fluid before and after UC-II supplementation

Analysis of Differentially Expressed Genes in Osteonecrosis of Femoral Head, Osteoarthritis, and Rheumatoid Arthritis by Integrated Microarray Analysis

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