Abstract
Whether osteoarthritis (OA) is a systemic metabolic disorder remains controversial. The aim of this study was to investigate the metabolic characteristics between plasma and knee joint fluid (JF) of patients with advanced OA using a differential correlation metabolic (DCM) networks approach. Plasma and JF were collected during the joint replacement surgery of patients with knee OA. The biological samples were pretreated with standard procedures for metabolite analysis. The metabolic profiling was conducted by means of liquid mass spectrometry coupled with a AbsoluteIDQ kit. A DCM network approach was adopted for analyzing the metabolomics data between the plasma and JF. The variation in the correlation of the pairwise metabolites was quantified across the plasma and JF samples, and networks analysis was used to characterize the difference in the correlations of the metabolites from the two sample types. Core metabolites that played an important role in the DCM networks were identified via topological analysis. One hundred advanced OA patients (50 men and 50 women) were included in this study, with an average age of 65.0 ± 7.6 years (65.6 ± 7.1 years for females and 64.4 ± 8.1 years for males) and a mean BMI of 32.6 ± 5.8 kg/m2 (33.4 ± 6.3 kg/m2 for females and 31.7 ± 5.3 kg/m2 for males). Age and BMI matched between the male and female groups. One hundred and forty-five nodes, 567 edges, and 131 nodes, 407 edges were found in the DCM networks (p < 0.05) of the female and male groups, respectively. Six metabolites in the female group and 5 metabolites in the male group were identified as key nodes in the network. There was a significant difference in the differential correlation metabolism networks of plasma and JF that may be related to local joint metabolism. Focusing on these key metabolites may help uncover the pathogenesis of knee OA. In addition, the differential metabolic correlation between plasma and JF mostly overlapped, indicating that these common correlations of pairwise metabolites may be a reflection of systemic characteristics of JF and that most significant correlation variations were just a result of "housekeeping” biological reactions.
Highlights
Osteoarthritis (OA) is a common orthopedic disease with no effective treatment in clinic. [1]
The differential correlation metabolic (DCM) network analysis approach was previously developed by our research team and was applied to calculate the correlation values of pairwise metabolites in different phenotypic region groups, a process followed by subtracting the correlation values and constructing the differential network by the significantly different pairwise metabolites [13]
Blood and joint fluid (JF) samples were collected from each participant
Summary
Osteoarthritis (OA) is a common orthopedic disease with no effective treatment in clinic. [1]. There are still some researchers who believe that OA should not considered a systemic disease, as it only affects the joints and not other organ systems [2,3,4]. Given the close relationship between JF and blood and joint tissues, blood samples are usually used in OA research based on the assumption that the metabolic characteristics between plasma and JF are similar [6]. This assumption has yet to be fully tested, and comprehensive investigations are needed. We studied the relationship between plasma and joint fluid based on absolute metabolite concentrations, found a modest relationship [7]
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