Objective:Osteoarthritis(OA)and sarcopenia are significant health concerns in the elderly,substantially impacting their daily activities and quality of life.However,the relationship between them remains poorly underst...Objective:Osteoarthritis(OA)and sarcopenia are significant health concerns in the elderly,substantially impacting their daily activities and quality of life.However,the relationship between them remains poorly understood.This study aims to uncover common biomarkers and pathways associated with both OA and sarcopenia.Methods:Gene expression profiles related to OA and sarcopenia were retrieved from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)between disease and control groups were identified using R software.Common DEGs were extracted via Venn diagram analysis.Gene ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses were conducted to identify biological processes and pathways associated with shared DEGs.Protein-protein interaction(PPI)networks were constructed,and candidate hub genes were ranked using the maximal clique centrality(MCC)algorithm.Further validation of hub gene expression was performed using 2 independent datasets.Receiver operating characteristic(ROC)curve analysis was used to evaluate the predictive value of key genes for OA and sarcopenia.Mouse models of OA and sarcopenia were established.Hematoxylin-eosin and Safranin O/Fast Green staining were used to validate the OA model.The sarcopenia model was validated via rotarod testing and quadriceps muscle mass measurement.Real-time reverse transcription PCR(real-time RT-PCR)was employed to assess the mRNA expression levels of candidate key genes in both models.Gene set enrichment analysis(GSEA)was conducted to identify pathways associated with the selected shared key genes in both diseases.Results:A total of 89 common DEGs were identified in the gene expression profiles of OA and sarcopenia,including 76 upregulated and 13 downregulated genes.These 89 DEGs were significantly enriched in protein digestion and absorption,the PI3K-Akt signaling pathway,and extracellular matrix-receptor interaction.PPI network analysis and MCC algorithm analysis of the 89 common DEGs identified the top 17 candidate hub genes.Based on the differential expression analysis of these 17 candidate hub genes in the validation datasets,AEBP1 and COL8A2 were ultimately selected as the common key genes for both diseases,both of which showed a significant upregulation trend in the disease groups(all P<0.05).The value of area under the curve(AUC)for AEBP1 and COL8A2 in the OA and sarcopenia datasets were all greater than 0.7,indicating that both genes have potential value in predicting OA and sarcopenia.Real-time RT-PCR results showed that the mRNA expression levels of AEBP1 and COL8A2 were significantly upregulated in the disease groups(all P<0.05),consistent with the results observed in the bioinformatics analysis.GSEA revealed that AEBP1 and COL8A2 were closely related to extracellular matrix-receptor interaction,ribosome,and oxidative phosphorylation in OA and sarcopenia.Conclusion:AEBP1 and COL8A2 have the potential to serve as common biomarkers for OA and sarcopenia.The extracellular matrix-receptor interaction pathway may represent a potential target for the prevention and treatment of both OA and sarcopenia.展开更多
目的了解中老年2型糖尿病(type 2 diabetes mellitus,T2DM)患者少肌性肥胖(sarcopenic obesity,SO)患病率及不同诊断方法之间的一致性。方法采用系统随机抽样法选取2016年1月至2018年3月于北京地区9家医院内分泌科就诊的≥50岁T2DM患者...目的了解中老年2型糖尿病(type 2 diabetes mellitus,T2DM)患者少肌性肥胖(sarcopenic obesity,SO)患病率及不同诊断方法之间的一致性。方法采用系统随机抽样法选取2016年1月至2018年3月于北京地区9家医院内分泌科就诊的≥50岁T2DM患者,使用生物阻抗法进行身体成分检测;根据2022年欧洲临床营养与代谢学会(European Society for Clinical Nutrition and Metabolism,ESPEN)和欧洲肥胖研究协会(European Association for the Study of Obesity,EASO)方法定义SO,另外3种方法通过肌少症和肥胖的组合进行诊断。肌少症使用2019年亚洲肌少症工作组(Asian Working Group for Sarcopenia,AWGS)建立的标准来定义,肥胖通过体脂(percent of body fat,PBF)、腰围(waist circumference,WC)和体质量指数(body mass index,BMI)来定义。卡方检验进行率的比较,Cohens kappa统计分析比较4种方法的诊断一致性。结果共纳入1125例T2DM受试者,男性586例,年龄[61.2(55.3,67.4)]岁;女性539例,年龄[62.0(56.3,68.1)岁]。使用ESPEN/EASO共识、AWGS+PBF、AWGS+WC和AWGS+BMI标准,中老年T2DM患者SO患病率分别为41.6%、20.4%、30.1%和18.8%。4种方法之间的诊断一致性存在异质性(κ:0.109~0.655)。ESPEN/EASO共识与AWGS+PBF诊断一致性良好(κ:0.655),AWGS+体脂与AWGS+BMI诊断一致性良好(κ:0.637),AWGS+WC与AWGS+BMI(κ:0.359)、与AWGS+PBF诊断一致性中等(κ:0.330)。结论中老年T2DM患者SO患病率高,患病率和诊断一致性在不同诊断方法中存在差异,ESPEN/EASO的共识诊断率最高,AWGS+BMI诊断率最低,ESPEN/EASO共识与AWGS+体脂具有良好的诊断一致性。展开更多
基金supported by the National Natural Science Foundation of China(82060418).
文摘Objective:Osteoarthritis(OA)and sarcopenia are significant health concerns in the elderly,substantially impacting their daily activities and quality of life.However,the relationship between them remains poorly understood.This study aims to uncover common biomarkers and pathways associated with both OA and sarcopenia.Methods:Gene expression profiles related to OA and sarcopenia were retrieved from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)between disease and control groups were identified using R software.Common DEGs were extracted via Venn diagram analysis.Gene ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses were conducted to identify biological processes and pathways associated with shared DEGs.Protein-protein interaction(PPI)networks were constructed,and candidate hub genes were ranked using the maximal clique centrality(MCC)algorithm.Further validation of hub gene expression was performed using 2 independent datasets.Receiver operating characteristic(ROC)curve analysis was used to evaluate the predictive value of key genes for OA and sarcopenia.Mouse models of OA and sarcopenia were established.Hematoxylin-eosin and Safranin O/Fast Green staining were used to validate the OA model.The sarcopenia model was validated via rotarod testing and quadriceps muscle mass measurement.Real-time reverse transcription PCR(real-time RT-PCR)was employed to assess the mRNA expression levels of candidate key genes in both models.Gene set enrichment analysis(GSEA)was conducted to identify pathways associated with the selected shared key genes in both diseases.Results:A total of 89 common DEGs were identified in the gene expression profiles of OA and sarcopenia,including 76 upregulated and 13 downregulated genes.These 89 DEGs were significantly enriched in protein digestion and absorption,the PI3K-Akt signaling pathway,and extracellular matrix-receptor interaction.PPI network analysis and MCC algorithm analysis of the 89 common DEGs identified the top 17 candidate hub genes.Based on the differential expression analysis of these 17 candidate hub genes in the validation datasets,AEBP1 and COL8A2 were ultimately selected as the common key genes for both diseases,both of which showed a significant upregulation trend in the disease groups(all P<0.05).The value of area under the curve(AUC)for AEBP1 and COL8A2 in the OA and sarcopenia datasets were all greater than 0.7,indicating that both genes have potential value in predicting OA and sarcopenia.Real-time RT-PCR results showed that the mRNA expression levels of AEBP1 and COL8A2 were significantly upregulated in the disease groups(all P<0.05),consistent with the results observed in the bioinformatics analysis.GSEA revealed that AEBP1 and COL8A2 were closely related to extracellular matrix-receptor interaction,ribosome,and oxidative phosphorylation in OA and sarcopenia.Conclusion:AEBP1 and COL8A2 have the potential to serve as common biomarkers for OA and sarcopenia.The extracellular matrix-receptor interaction pathway may represent a potential target for the prevention and treatment of both OA and sarcopenia.
文摘目的了解中老年2型糖尿病(type 2 diabetes mellitus,T2DM)患者少肌性肥胖(sarcopenic obesity,SO)患病率及不同诊断方法之间的一致性。方法采用系统随机抽样法选取2016年1月至2018年3月于北京地区9家医院内分泌科就诊的≥50岁T2DM患者,使用生物阻抗法进行身体成分检测;根据2022年欧洲临床营养与代谢学会(European Society for Clinical Nutrition and Metabolism,ESPEN)和欧洲肥胖研究协会(European Association for the Study of Obesity,EASO)方法定义SO,另外3种方法通过肌少症和肥胖的组合进行诊断。肌少症使用2019年亚洲肌少症工作组(Asian Working Group for Sarcopenia,AWGS)建立的标准来定义,肥胖通过体脂(percent of body fat,PBF)、腰围(waist circumference,WC)和体质量指数(body mass index,BMI)来定义。卡方检验进行率的比较,Cohens kappa统计分析比较4种方法的诊断一致性。结果共纳入1125例T2DM受试者,男性586例,年龄[61.2(55.3,67.4)]岁;女性539例,年龄[62.0(56.3,68.1)岁]。使用ESPEN/EASO共识、AWGS+PBF、AWGS+WC和AWGS+BMI标准,中老年T2DM患者SO患病率分别为41.6%、20.4%、30.1%和18.8%。4种方法之间的诊断一致性存在异质性(κ:0.109~0.655)。ESPEN/EASO共识与AWGS+PBF诊断一致性良好(κ:0.655),AWGS+体脂与AWGS+BMI诊断一致性良好(κ:0.637),AWGS+WC与AWGS+BMI(κ:0.359)、与AWGS+PBF诊断一致性中等(κ:0.330)。结论中老年T2DM患者SO患病率高,患病率和诊断一致性在不同诊断方法中存在差异,ESPEN/EASO的共识诊断率最高,AWGS+BMI诊断率最低,ESPEN/EASO共识与AWGS+体脂具有良好的诊断一致性。
