• Medicine · May 2023

    Comparisons of gene expression between peripheral blood mononuclear cells and bone tissue in osteoporosis.

    • Lihua Xie, Eryou Feng, Shengqiang Li, Hao Chai, Juan Chen, Li Li, and Jirong Ge.
    • Key Research Laboratory of Osteoporosis Syndrome Genomics, Fujian Academy of Chinese Medical Sciences, Fuzhou, China.
    • Medicine (Baltimore). 2023 May 19; 102 (20): e33829e33829.

    AbstractOsteoporosis (OP) is one of the major public health problems in the world. However, the biomarkers between the peripheral blood mononuclear cells (PBMs) and bone tissue for prognosis of OP have not been well characterized. This study aimed to explore the similarities and differences of the gene expression profiles between the PBMs and bone tissue and identify potential genes, transcription factors (TFs) and hub proteins involved in OP. The patients were enrolled as an experimental group, and healthy subjects served as normal controls. Human whole-genome expression chips were used to analyze gene expression profiles from PBMs and bone tissue. And the differentially expressed genes (DEGs) were subsequently studied using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis. The above DEGs were constructed into protein-protein interaction network. Finally, TF-DEGs regulation networks were constructed. Microarray analysis revealed that 226 DEGs were identified between OP and normal controls in the PBMs, while 2295 DEGs were identified in the bone tissue. And 13 common DEGs were obtained by comparing the 2 tissues. The Gene Ontology analysis indicated that DEGs in the PBMs were more involved in immune response, while DEGs in bone were more involved in renal response and urea transmembrane transport. And the Kyoto Encyclopedia of Genes and Genomes analysis indicated almost all of the pathways in the PBMs were overlapped with those in the bone tissue. Furthermore, protein-protein interaction network presented 6 hub proteins: PI3K1, APP, GNB5, FPR2, GNG13, and PLCG1. APP has been found to be associated with OP. Finally, 5 key TFs were identified by TF-DEGs regulation networks analysis (CREB1, RUNX1, STAT3, CREBBP, and GLI1) and were supposed to be associated with OP. This study enhanced our understanding of the pathogenesis of OP. PI3K1, GNB5, FPR2, GNG13, and PLCG1 might be the potential targets of OP.Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.

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