Bangzhi Li, Long Shi, Qiong Wang, Yang Li, Liang Zhao, Rongcan Zhao, Yanjin Wang, Yingjie Zhou, Shan Gu
{"title":"Identification of Mitochondria- and Macrophage Activation-Related Hub Genes in Sarcopenia.","authors":"Bangzhi Li, Long Shi, Qiong Wang, Yang Li, Liang Zhao, Rongcan Zhao, Yanjin Wang, Yingjie Zhou, Shan Gu","doi":"10.1049/syb2.70081","DOIUrl":null,"url":null,"abstract":"<p><p>To explore the hub genes and pathways associated with sarcopenia progression from the perspective of mitochondrial dysfunction and macrophage activation. The GEO datasets GSE8479, GSE1428 and GSE136344 were obtained from the GEO database. Mitochondria-related genes (MRGs) and macrophage activation-related genes (MARGs) were identified. Functional enrichment analyses, PPI analysis, diagnostic model construction, molecular subtyping and ssGSEA-based immune enrichment analysis were performed. Key genes were further validated by RT-qPCR. A total of 62 mitochondria- and macrophage activation-related differentially expressed genes (M&MARDEGs) were identified. Nine key genes (IGF1, FTL, MAPK8, MAPK9, TF, CREB1, FAS, VEGFA and NFKB1) were retained in the final diagnostic model. Immune enrichment analysis suggested distinct immune-related transcriptional characteristics among different risk groups and molecular subtypes. RT-qPCR validation demonstrated that IGF1, FAS and MAPK9 were significantly downregulated, whereas FTL, TF, CREB1 and NFKB1 were significantly upregulated in the sarcopenia model group. MAPK8 and VEGFA showed decreasing trends without statistical significance. Integrated transcriptomic analysis identified key genes potentially associated with sarcopenia through the intersection of mitochondrial dysfunction and macrophage activation. These findings provide insights into the molecular characteristics of sarcopenia and may offer candidate targets for future mechanistic and translational studies.</p>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":"20 1","pages":"e70081"},"PeriodicalIF":1.9000,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13379267/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Systems Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1049/syb2.70081","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
To explore the hub genes and pathways associated with sarcopenia progression from the perspective of mitochondrial dysfunction and macrophage activation. The GEO datasets GSE8479, GSE1428 and GSE136344 were obtained from the GEO database. Mitochondria-related genes (MRGs) and macrophage activation-related genes (MARGs) were identified. Functional enrichment analyses, PPI analysis, diagnostic model construction, molecular subtyping and ssGSEA-based immune enrichment analysis were performed. Key genes were further validated by RT-qPCR. A total of 62 mitochondria- and macrophage activation-related differentially expressed genes (M&MARDEGs) were identified. Nine key genes (IGF1, FTL, MAPK8, MAPK9, TF, CREB1, FAS, VEGFA and NFKB1) were retained in the final diagnostic model. Immune enrichment analysis suggested distinct immune-related transcriptional characteristics among different risk groups and molecular subtypes. RT-qPCR validation demonstrated that IGF1, FAS and MAPK9 were significantly downregulated, whereas FTL, TF, CREB1 and NFKB1 were significantly upregulated in the sarcopenia model group. MAPK8 and VEGFA showed decreasing trends without statistical significance. Integrated transcriptomic analysis identified key genes potentially associated with sarcopenia through the intersection of mitochondrial dysfunction and macrophage activation. These findings provide insights into the molecular characteristics of sarcopenia and may offer candidate targets for future mechanistic and translational studies.
期刊介绍:
IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells.
The scope includes the following topics:
Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.