{"title":"基于糖酵解的基因特征与骨关节炎患者的免疫浸润密切相关。","authors":"Ziyi Chen, Yinghui Hua","doi":"10.1016/j.cyto.2023.156377","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Osteoarthritis (OA) is a degenerative arthritis with high levels of clinical heterogeneity. Aberrant metabolism such as shifting from oxidative phosphorylation to glycolysis is a response to changes in the inflammatory microenvironment of OA. Therefore, there is a pressing need to identify novel glycolysis regulators during OA progression.</p></div><div><h3>Methods</h3><p>We systematically studied glycolysis patterns mediated by 141 glycolysis regulators in 74 human synovial samples and discussed the characteristics of the immune microenvironment modified by glycolysis. The random forest (RF) method was applied to screen candidate hub glycolysis regulators in OA. RT-qPCR was performed to validate these key regulators. Then distinct glycolysis patterns were identified, and systematic correlation between these glycolysis patterns and immune cell infiltration was analyzed. The glycolysis score was constructed to quantify glycolysis patterns together with immune infiltration of individual OA patient.</p></div><div><h3>Results</h3><p>56 glycolysis-related differentially expressed genes (DEGs) were identified between OA and non-OA samples. <em>STC1, VEGFA, KDELR3, DDIT4</em> and <em>PGAM1</em> were selected as candidate genes to predict the probability of OA. Two glycolysis patterns in OA were identified. Glycolysis cluster A with higher glycolysis score was related to an inflamed phenotype.</p></div><div><h3>Conclusions</h3><p>Taken together, our results established a glycolysis-based genetic signature for OA, guided in-depth studies on the metabolic mechanism of OA, and facilitated to explore new clinical treatment strategies.</p></div>","PeriodicalId":297,"journal":{"name":"Cytokine","volume":"171 ","pages":"Article 156377"},"PeriodicalIF":3.7000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Gene signature based on glycolysis is closely related to immune infiltration of patients with osteoarthritis\",\"authors\":\"Ziyi Chen, Yinghui Hua\",\"doi\":\"10.1016/j.cyto.2023.156377\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Osteoarthritis (OA) is a degenerative arthritis with high levels of clinical heterogeneity. Aberrant metabolism such as shifting from oxidative phosphorylation to glycolysis is a response to changes in the inflammatory microenvironment of OA. Therefore, there is a pressing need to identify novel glycolysis regulators during OA progression.</p></div><div><h3>Methods</h3><p>We systematically studied glycolysis patterns mediated by 141 glycolysis regulators in 74 human synovial samples and discussed the characteristics of the immune microenvironment modified by glycolysis. The random forest (RF) method was applied to screen candidate hub glycolysis regulators in OA. RT-qPCR was performed to validate these key regulators. Then distinct glycolysis patterns were identified, and systematic correlation between these glycolysis patterns and immune cell infiltration was analyzed. The glycolysis score was constructed to quantify glycolysis patterns together with immune infiltration of individual OA patient.</p></div><div><h3>Results</h3><p>56 glycolysis-related differentially expressed genes (DEGs) were identified between OA and non-OA samples. <em>STC1, VEGFA, KDELR3, DDIT4</em> and <em>PGAM1</em> were selected as candidate genes to predict the probability of OA. Two glycolysis patterns in OA were identified. Glycolysis cluster A with higher glycolysis score was related to an inflamed phenotype.</p></div><div><h3>Conclusions</h3><p>Taken together, our results established a glycolysis-based genetic signature for OA, guided in-depth studies on the metabolic mechanism of OA, and facilitated to explore new clinical treatment strategies.</p></div>\",\"PeriodicalId\":297,\"journal\":{\"name\":\"Cytokine\",\"volume\":\"171 \",\"pages\":\"Article 156377\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2023-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cytokine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1043466623002557\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cytokine","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1043466623002557","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Gene signature based on glycolysis is closely related to immune infiltration of patients with osteoarthritis
Background
Osteoarthritis (OA) is a degenerative arthritis with high levels of clinical heterogeneity. Aberrant metabolism such as shifting from oxidative phosphorylation to glycolysis is a response to changes in the inflammatory microenvironment of OA. Therefore, there is a pressing need to identify novel glycolysis regulators during OA progression.
Methods
We systematically studied glycolysis patterns mediated by 141 glycolysis regulators in 74 human synovial samples and discussed the characteristics of the immune microenvironment modified by glycolysis. The random forest (RF) method was applied to screen candidate hub glycolysis regulators in OA. RT-qPCR was performed to validate these key regulators. Then distinct glycolysis patterns were identified, and systematic correlation between these glycolysis patterns and immune cell infiltration was analyzed. The glycolysis score was constructed to quantify glycolysis patterns together with immune infiltration of individual OA patient.
Results
56 glycolysis-related differentially expressed genes (DEGs) were identified between OA and non-OA samples. STC1, VEGFA, KDELR3, DDIT4 and PGAM1 were selected as candidate genes to predict the probability of OA. Two glycolysis patterns in OA were identified. Glycolysis cluster A with higher glycolysis score was related to an inflamed phenotype.
Conclusions
Taken together, our results established a glycolysis-based genetic signature for OA, guided in-depth studies on the metabolic mechanism of OA, and facilitated to explore new clinical treatment strategies.
期刊介绍:
The journal Cytokine has an open access mirror journal Cytokine: X, sharing the same aims and scope, editorial team, submission system and rigorous peer review.
* Devoted exclusively to the study of the molecular biology, genetics, biochemistry, immunology, genome-wide association studies, pathobiology, diagnostic and clinical applications of all known interleukins, hematopoietic factors, growth factors, cytotoxins, interferons, new cytokines, and chemokines, Cytokine provides comprehensive coverage of cytokines and their mechanisms of actions, 12 times a year by publishing original high quality refereed scientific papers from prominent investigators in both the academic and industrial sectors.
We will publish 3 major types of manuscripts:
1) Original manuscripts describing research results.
2) Basic and clinical reviews describing cytokine actions and regulation.
3) Short commentaries/perspectives on recently published aspects of cytokines, pathogenesis and clinical results.