Bioinformatics analysis of potential biomarkers for primary osteoporosis

doi:10.12307/2025.314

Abstract

Abstract: BACKGROUND: Primary osteoporosis has a high incidence, but the pathogenesis is not fully understood. Currently, there is a lack of effective early screening indicators and treatment programs.
OBJECTIVE: To further explore the mechanism of primary osteoporosis through comprehensive bioinformatics analysis.

METHODS: The primary osteoporosis data were obtained from the gene expression omnibus (GEO) database, and the differentially expressed genes were screened for Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. In addition, the differentially expressed genes were subjected to protein-protein interaction network to determine the core genes related to primary osteoporosis, and the least absolute shrinkage and selection operator algorithm was used to identify and verify the primary osteoporosis-related biomarkers. Immune cell correlation analysis, gene enrichment analysis and drug target network analysis were performed. Finally, the biomarkers were validated using qPCR assay.
RESULTS AND CONCLUSION: A total of 126 differentially expressed genes and 5 biomarkers including prostaglandins, epidermal growth factor receptor, mitogen-activated protein kinase 3, transforming growth factor B1, and retinoblastoma gene 1 were obtained in this study. GO analysis showed that differentially expressed genes were mainly concentrated in the cellular response to oxidative stress and the regulation of autophagy. KEGG analysis showed that autophagy and senescence pathways were mainly involved. Immunoassay of biomarkers showed that prostaglandins, retinoblastoma gene 1, and mitogen-activated protein kinase 3 were closely related to immune cells. Gene enrichment analysis showed that biomarkers were associated with immune-related pathways. Drug target network analysis showed that the five biomarkers were associated with primary osteoporosis drugs. The results of qPCR showed that the expression of prostaglandins, epidermal growth factor receptor, mitogen-activated protein kinase 3, and transforming growth factor B1 in the primary osteoporosis sample was significantly increased compared with the control sample (P < 0.001), while the expression of retinoblastoma gene 1 in the primary osteoporosis sample was significantly decreased compared with the control sample (P < 0.001). Overall, the study screened and validated five potential biomarkers of primary osteoporosis, providing a reference basis for further in-depth investigation of the pathogenesis, early screening and diagnosis, and targeted treatment of primary osteoporosis.

中国组织工程研究杂志出版内容重点：组织构建；骨细胞；软骨细胞；细胞培养；成纤维细胞；血管内皮细胞；骨质疏松；组织工程

Key words:

primary osteoporosis, biomarker, bioinformatics, drug target network, protein-protein interaction network

CLC Number:

Zhao Jiacheng, Ren Shiqi, Zhu Qin, Liu Jiajia, Zhu Xiang, Yang Yang. Bioinformatics analysis of potential biomarkers for primary osteoporosis[J]. Chinese Journal of Tissue Engineering Research, 2025, 29(8): 1741-1750.

Figures/Tables 10

对细胞外刺激的反应、细胞对氧化应激的反应以及自噬的调节等生物过程中发挥作用，在细胞组分中，与自噬体、核被膜以及过氧物酶体等；在分子功能中，主要在DNA结合转录因子结合、泛素蛋白连接酶结合以及泛素样蛋白连接酶结合等发挥作用。京都基因和基因组百科全书的生物学机制分析显示，交集基因主要聚集在人巨细胞病毒感染、自噬以及细胞衰老等信号通路中。 2.3 蛋白质相互作用网络分析结果使用STRING数据库构建了原发性骨质疏松中与核心差异基因相互作用的潜在蛋白质作用网络，见图3。结果中显示位于网络中心的核心基因影响其他基因在生物系统中的关系，共包括谷氨酸-半胱氨酸连接酶催化亚基、丝裂原活化蛋白激酶14、赖氨酸脱甲基酶6B及小鼠双微体2等27个核心基因，最后选取该网络中的27个核心基因进行生物标志物筛选。 2.4 生物标志物的筛选与验证结果该研究通过最小绝对收缩选择算子逻辑回归算法从27个核心基因中鉴定出前列腺素、表皮生长因子受体、丝裂原活化蛋白激酶3、转化生长因子B1和视网膜母细胞瘤基因1等5个原发性骨质疏松相关的生物标志物，见图4A。受试者工作特征分析曲线显示出它们具有较高的精确性，其中前列腺素的曲线下面积为1.000，表皮生长因子受体的曲线下面积为0.950，丝裂原活化蛋白激酶3的曲线下面积为1.000，转化生长因子B1的曲线下面积为1.000，以及视网膜母细胞瘤基因1的曲线下面积为1.000，见图4B-F。这些生物标志物在对照组即正常组织中与实验组即原发性骨质疏松组织中的差异表达分析显示，实验组中前列腺素、表皮生长因子受体、丝裂原活化蛋白激酶3以及转化生长因子B1的表达水平均明显高于对照组样本(P < 0.05)，见图4G-J；而视网膜母细胞瘤基因1在实验组表达量明显低于对照组样本(P < 0.05)，见图4K。 2.5 生物标志物的免疫分析结果该研究中免疫分析结果表明，细胞免疫在原发性骨质疏松中起重要作用。通过CIBERSORT算法分析生物标志物在不同免疫细胞浸润情况，表皮生长因子受体与辅助型T细胞1密切关联，视网膜母细胞瘤基因1在巨噬细胞中显著聚集见图5。 2.6 生物标志物的基因富集分析结果将原发性骨质疏松的生物标志物进行基因富集分析。前列腺素的分析结果表明，其高表达可能影响蛋白酶体和EB病毒感染等方面，低表达可能与抗坏血酸和醛达酸代谢等方面有关，见图6A。表皮生长因子受体的分析结果表明，其高表达可能影响同种异体移植排斥及自身免疫性甲状腺疾病等，低表达可能影响移植物抗宿主疾病等，见图6B。丝裂原活化蛋白激酶3的分析结果表明其与JAK?STAT信号通路、同种异体移植排斥及爱帕琳肽信号通路相关，见图6C。转化生长因子B1的分析结果表明，其与同种异体移植排斥、抗坏血酸和醛达酸代谢、自身免疫性甲状腺疾病等通路相"

References

[1] LEBOFF MS, GREENSPAN SL, INSOGNA KL, et al. The clinician’s guide to prevention and treatment of osteoporosis. Osteoporos Int. 2022;33(10):2049-2102.
[2] BROWN JP. Long-term treatment of postmenopausal osteoporosis. Endocrinol Metab (Seoul). 2021;36(3):544-552.
[3] 武瑞骐,周毅,夏天,等.类风湿性关节炎与骨质疏松症和骨密度关系的孟德尔随机化分析[J].中国组织工程研究,2024,28(23): 3715-3721.
[4] YONG EL, LOGAN S. Menopausal osteoporosis: screening, prevention and treatment. Singapore Med J. 2021;62(4):159-166.
[5] LI S, CHEN B, CHEN H, et al. Analysis of potential genetic biomarkers and molecular mechanism of smoking-related postmenopausal osteoporosis using weighted gene co-expression network analysis and machine learning. PLoS One. 2021;16(9): e0257343.
[6] AIBAR-ALMAZAN A, VOLTES-MARTINEZ A, CASTELLOTE-CABALLERO Y, et al. Current status of the diagnosis and management of osteoporosis. Int J Mol Sci. 2022;23(16):9465.
[7] HU Y, HAN J, DING S, et al. Identification of ferroptosis-associated biomarkers for the potential diagnosis and treatment of postmenopausal osteoporosis. Front Endocrinol (Lausanne). 2022;13:986384.
[8] DEMPSTER DW, SHANE E, HORBERT W, et al. A simple method for correlative light and scanning electron microscopy of human iliac crest bone biopsies: qualitative observations in normal and osteoporotic subjects. J Bone Miner Res. 1986;1(1):15-21.
[9] RIGGS BL, KHOSLA S, ATKINSON EJ, et al. Evidence that type I osteoporosis results from enhanced responsiveness of bone to estrogen deficiency. Osteoporos Int. 2003;14(9):728-733.
[10] SRIVASTAVA M, DEAL C. Osteoporosis in elderly: prevention and treatment. Clin Geriatr Med. 2002;18(3):529-555.
[11] LI Y, SI Y, MA Y, et al. Application and prospect of metabolomics in the early diagnosis of osteoporosis: a narrative review. Bioanalysis. 2023;15(22):1369-79.
[12] PRESTWOOD KM, PILBEAM CC, RAISZ LG. Treatment of osteoporosis. Annu Rev Med. 1995;46:249-256.
[13] CHEUNG AM, GIANGREGORIO L. Mechanical stimuli and bone health: what is the evidence?. Curr Opin Rheumatol. 2012;24(5):561-566.
[14] WANG CG, HU YH, SU SL, et al. LncRNA DANCR and miR-320a suppressed osteogenic differentiation in osteoporosis by directly inhibiting the Wnt/beta-catenin signaling pathway. Exp Mol Med. 2020;52(8):1310-1325.
[15] YOSHIDA G, KAWABATA T, TAKAMATSU H, et al. Degradation of the NOTCH intracellular domain by elevated autophagy in osteoblasts promotes osteoblast differentiation and alleviates osteoporosis. Autophagy. 2022;18(10):2323-2332.
[16] HUANG H, HE YM, LIN MM, et al. P2X7Rs: new therapeutic targets for osteoporosis. Purinergic Signal. 2023;19(1):207-219.
[17] AYERS C, KANSAGARA D, LAZUR B, et al. Effectiveness and safety of treatments to prevent fractures in people with low bone mass or primary osteoporosis: a living systematic review and network meta-analysis for the american college of physicians. Ann Intern Med. 2023;176(2):182-195.
[18] KIM W K, MELITON V, BOURQUARD N, et al. Hedgehog signaling and osteogenic differentiation in multipotent bone marrow stromal cells are inhibited by oxidative stress. J Cell Biochem. 2010;111(5):1199-1209.
[19] H DEHKORD IM, TASHAKOR A, O’CONNELL E, et al. Apoptosome-dependent myotube formation involves activation of caspase-3 in differentiating myoblasts. Cell Death Dis. 2020;11(5):308.
[20] LI F, SUN X, MA J, et al. Naringin prevents ovariectomy-induced osteoporosis and promotes osteoclasts apoptosis through the mitochondria-mediated apoptosis pathway. Biochem Biophys Res Commun. 2014;452(3):629-635.
[21] ZHANG C, LI H, LI J, et al. Oxidative stress: a common pathological state in a high-risk population for osteoporosis. Biomed Pharmacother. 2023;163:114834.
[22] SANCHEZ-RODRIGUEZ MA, RUIZ-RAMOS M, CORREA-MUNOZ E, et al. Oxidative stress as a risk factor for osteoporosis in elderly Mexicans as characterized by antioxidant enzymes. BMC Musculoskelet Disord. 2007;8:124.
[23] LIU Y, WANG C, WANG G, et al. Loureirin B suppresses RANKL-induced osteoclastogenesis and ovariectomized osteoporosis via attenuating NFATc1 and ROS activities. Theranostics. 2019;9(16):4648-4662.
[24] LI H, HUANG C, ZHU J, et al. Lutein suppresses oxidative stress and inflammation by nrf2 activation in an osteoporosis rat model. Med Sci Monit. 2018;24:5071-5075.
[25] RAUWEL B, DEGBOE Y, DIALLO K, et al. Inhibition of osteoclastogenesis by the RNA-binding protein QKI5: a novel approach to protect from bone resorption. J Bone Miner Res. 2020;35(4):753-765.
[26] CHANDRA A, LAGNADO AB, FARR JN, et al. Targeted reduction of senescent cell burden alleviates focal radiotherapy-related bone loss. J Bone Miner Res. 2020;35(6):1119-1131.
[27] FARR JN, XU M, WEIVODA MM, et al. Targeting cellular senescence prevents age-related bone loss in mice. Nat Med. 2017;23(9):1072-10729.
[28] GUAN JL, SIMON AK, PRESCOTT M, et al. Autophagy in stem cells. Autophagy. 2013;9(6): 830-849.
[29] LI H, LI D, MA Z, et al. Defective autophagy in osteoblasts induces endoplasmic reticulum stress and causes remarkable bone loss. Autophagy. 2018;14(10):1726-1741.
[30] YIN X, ZHOU C, LI J, et al. Autophagy in bone homeostasis and the onset of osteoporosis. Bone Res. 2019;7:28.
[31] SHAPIRO IM, LAYFIELD R, LOTZ M, et al. Boning up on autophagy: the role of autophagy in skeletal biology. Autophagy. 2014;10(1):7-19.
[32] ZHU C, SHEN S, ZHANG S, et al. Autophagy in bone remodeling: a regulator of oxidative stress. Front Endocrinol (Lausanne). 2022;13: 898634.
[33] WU M, ZHANG P. EGFR-mediated autophagy in tumourigenesis and therapeutic resistance. Cancer Lett. 2020;469:207-216.
[34] LIANG C, XU J, MENG Q, et al. TGFB1-induced autophagy affects the pattern of pancreatic cancer progression in distinct ways depending on SMAD4 status. Autophagy. 2020;16(3):486-500.
[35] XIAO S, LIU N, YANG X, et al. Polygalacin D suppresses esophageal squamous cell carcinoma growth and metastasis through regulating miR-142-5p/Nrf2 axis. Free Radic Biol Med. 2021;164:58-75.
[36] RUBY M, GIFFORD CC, PANDEY R, et al. Autophagy as a therapeutic target for chronic kidney disease and the roles of TGF-beta1 in autophagy and kidney fibrosis. Cells. 2023. doi:10.3390/cells12030412.
[37] TIAN L, XIAO H, LI M, et al. A novel Sprouty4-ERK1/2-Wnt/beta-catenin regulatory loop in marrow stromal progenitor cells controls osteogenic and adipogenic differentiation. Metabolism. 2020;105:154189.
[38] LIU F, SONG C, CAI W, et al. Shared mechanisms and crosstalk of COVID-19 and osteoporosis via vitamin D. Sci Rep. 2022;12(1):18147.
[39] LINDER M, HECKING M, GLITZNER E, et al. EGFR controls bone development by negatively regulating mTOR-signaling during osteoblast differentiation. Cell Death Differ. 2018;25(6):1094-106.
[40] ROBLING AG, BONEWALD LF. The osteocyte: new insights. Annu Rev Physiol. 2020;82:485-506.
[41] YUE J, LOPEZ J M. Understanding MAPK signaling pathways in apoptosis. Int J Mol Sci. 2020;21(7):2346.
[42] TANG L, WU M, LU S, et al. Fgf9 Negatively regulates bone mass by inhibiting osteogenesis and promoting osteoclastogenesis Via MAPK and PI3K/AKT signaling. J Bone Miner Res. 2021;36(4):779-791.
[43] 覃浩,亢腾,刘钢.长链非编码RNA通过p38MAPK信号通路直接或间接影响骨质疏松症[J].中国组织工程研究,2025,29(1):175-184.
[44] LIU Q, XU YC, SHUAI ZW. Mir-142-3P regulates MAPK protein family by inhibiting 14-3-3η to enhance bone marrow mesenchymal stem cells osteogenesis. Sci Rep. 2023;13(1):22862.
[45] TAKAHARA T, TSUYUKI T, SATOU A, et al. TGFB1 mRNA expression is associated with poor prognosis and specific features of inflammation in ccRCC. Virchows Arch. 2022;480(3):635-643.
[46] WANG YW, LIN WY, WU FJ, et al. Unveiling the transcriptomic landscape and the potential antagonist feedback mechanisms of TGF-beta superfamily signaling module in bone and osteoporosis. Cell Commun Signal. 2022; 20(1):190.
[47] SASAKI N, ITAKURA Y, MOHSIN S, et al. Cell surface and functional features of cortical bone stem cells. Int J Mol Sci. 2021;22(21):11849.
[48] TAKEUCHI Y, NAKAYAMA K, MATSUMOTO T. Differentiation and cell surface expression of transforming growth factor-beta receptors are regulated by interaction with matrix collagen in murine osteoblastic cells. J Biol Chem. 1996; 271(7):3938-3944.
[49] KNUDSEN ES, PRUITT SC, HERSHBERGER PA, et al. Cell cycle and beyond: exploiting new RB1 controlled mechanisms for cancer therapy. Trends Cancer. 2019;5(5):308-324.
[50] THOMAS DM, CARTY SA, PISCOPO DM, et al. The retinoblastoma protein acts as a transcriptional coactivator required for osteogenic differentiation. Mol Cell. 2001;8(2):303-216.
[51] CALO E, QUINTERO-ESTADES JA, DANIELIAN PS, et al. Rb regulates fate choice and lineage commitment in vivo. Nature. 2010; 466(7310):1110-1114.
[52] HANAU S, HELLIWELL JR. 6-Phosphogluconate dehydrogenase and its crystal structures. Acta Crystallogr F Struct Biol Commun. 2022; 78(Pt 3):96-112.