Metabolic networks of plasma and joint fluid base on differential correlation.
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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2021-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0247191 |
| _version_ | 1818743192189665280 |
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| author | Bingyong Xu Hong Su Ruya Wang Yixiao Wang Weidong Zhang |
| author_facet | Bingyong Xu Hong Su Ruya Wang Yixiao Wang Weidong Zhang |
| author_sort | Bingyong Xu |
| collection | DOAJ |
| description | 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. |
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| format | Article |
| id | doaj.art-958275b624fc49fb96ab4ebb4802f03f |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-18T02:24:30Z |
| publishDate | 2021-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-958275b624fc49fb96ab4ebb4802f03f2022-12-21T21:24:05ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01162e024719110.1371/journal.pone.0247191Metabolic networks of plasma and joint fluid base on differential correlation.Bingyong XuHong SuRuya WangYixiao WangWeidong ZhangWhether 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.https://doi.org/10.1371/journal.pone.0247191 |
| spellingShingle | Bingyong Xu Hong Su Ruya Wang Yixiao Wang Weidong Zhang Metabolic networks of plasma and joint fluid base on differential correlation. PLoS ONE |
| title | Metabolic networks of plasma and joint fluid base on differential correlation. |
| title_full | Metabolic networks of plasma and joint fluid base on differential correlation. |
| title_fullStr | Metabolic networks of plasma and joint fluid base on differential correlation. |
| title_full_unstemmed | Metabolic networks of plasma and joint fluid base on differential correlation. |
| title_short | Metabolic networks of plasma and joint fluid base on differential correlation. |
| title_sort | metabolic networks of plasma and joint fluid base on differential correlation |
| url | https://doi.org/10.1371/journal.pone.0247191 |
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