Osteoporosis (OP) and sarcopenia (SP) are multifactorial complex disorders with tight bidirectional correlations in their pathogeneses, which creates an urgent demand for therapeutic regimens targeting their shared signaling pathways. This study adopted an integrated bioinformatics strategy to excavate the core molecular pathways common to OP and SP, and screen candidate drugs for repurposing. Seed genes associated with the two disorders were collected from the NCBI database and published literatures. A protein-protein interaction (PPI) network was constructed via STRING and visualized with Cytoscape 3.9.1. Key modules and hub genes were identified through network analysis and Gene Ontology enrichment analysis. miRWalk and miRNet were utilized to predict microRNAs targeting hub genes, and DGIDB database was adopted to retrieve candidate therapeutic agents. Network analysis identified seven immune-related functional modules and ten hub genes including IL6 and TNF, which mainly mediate inflammatory responses and cytokine activities. A total of 20 repurposable drug candidates were obtained, among which nine have been applied for osteoporosis treatment, and the other eleven anti-inflammatory drugs are capable of simultaneously alleviating both OP and SP. Six microRNAs regulating hub genes were also predicted, which require further experimental verification. This research clarifies the shared inflammatory pathways of OP and SP and screens multiple agents with repurposing value, offering novel theoretical references for the combined clinical treatment of the two co-morbid diseases.

Haodan Liu, Changli Wang, Fangfang Zhang, Guangbin Ye,  Ruirui Yang, Cheng Zhang, Xuan Li, Xiaoyun Bin. Identification of Key Genes and Metabolic Pathways in Osteoporosis and Sarcopenia Based on Transcriptome Data for Drug Repurposing. International Journal of Frontiers in Medicine (2026), Vol. 8, Issue 2: 125-142. https://doi.org/10.25236/IJFM.2026.080215.

[1] Llorente I, García-Castañeda N, Valero C, et al. Osteoporosis in Rheumatoid Arthritis: Dangerous Liaisons[J]. Frontiers in Medicine, 2020,7:601618.DOI:10.3389/fmed.2020.601618.

[2] Xu G, Zhao J, Liu F, et al. Features of osteoporosis in male patients with bronchiectasis, a cross-sectional study[J]. Journal of Thoracic Disease, 2023,15(3):1177-1185.DOI:10.21037/jtd-22-887.

[3] Yalaev B I, Khusainova R I. Epigenetic regulation of bone remodeling and its role in the pathogenesis of primary osteoporosis[J]. Vavilov Journal of Genetics and Breeding, 2023,27(4):401-410. DOI:10.18699/VJGB-23-48.

[4] Komatsu N, Takayanagi H. Mechanisms of joint destruction in rheumatoid arthritis - immune  cell-fibroblast-bone interactions[J]. Nat Rev Rheumatol, 2022,18(7):415-429.DOI:10.1038/s41584-022-00793-5.

[5] Stavre Z, Kim J, Yang Y, et al. Schnurri-3 inhibition suppresses bone and joint damage in models of rheumatoid arthritis[J]. Proceedings of the National Academy of Sciences, 2023, 120(19):e2076948176. DOI:10.1073/pnas.2218019120.

[6] Angela S, Fadhilah G, Hsiao W W, et al. Nanomaterials in the treatment and diagnosis of rheumatoid arthritis: Advanced approaches[J]. SLAS Technol, 2024,29(4):100146. DOI:10.1016/j.slast.2024.100146.

[7] Yang Y, Lu L, Wang J, et al. Tubson-2 decoction ameliorates rheumatoid arthritis complicated with osteoporosis in CIA rats involving isochlorogenic acid A regulating IL-17/MAPK pathway[J]. Phytomedicine (Stuttgart), 2023,116:154875.DOI:10.1016/j.phymed.2023.154875.

[8] Centofanti F, Santoro M, Marini M, et al. Identification of Aberrantly-Expressed Long Non-Coding RNAs in Osteoblastic Cells from Osteoporotic Patients[J]. Biomedicines, 2020,8(3):65. DOI:10.3390/biomedicines8030065.

[9] Perez-Edo L, Ciria Recasens M, Castelo-Branco C, et al. Management of osteoporosis in general practice: a cross-sectional survey of primary care practitioners in Spain[J]. Osteoporos Int, 2004, 15(3):252-257.DOI:10.1007/s00198-003-1569-y.

[10] Wang H, Luo Y, Wang H, et al. Mechanistic advances in osteoporosis and anti‐osteoporosis therapies[J]. MedComm (2020), 2023,4(3):e244.DOI:10.1002/mco2.244.

[11] Cruz-Jentoft A J, Bahat G, Bauer J, et al. Sarcopenia: revised European consensus on definition and diagnosis[J]. Age and Ageing, 2019,48(1):16-31.DOI:10.1093/ageing/afy169.

[12] Oliveira A, Vaz C. The role of sarcopenia in the risk of osteoporotic hip fracture[J]. Clin Rheumatol, 2015,34(10):1673-1680.DOI:10.1007/s10067-015-2943-9.

[13] Petermann-Rocha F, Balntzi V, Gray S R, et al. Global prevalence of sarcopenia and severe sarcopenia: a systematic review and meta-analysis[J]. J Cachexia Sarcopenia Muscle, 2022,13(1):86-99. DOI:10.1002/jcsm.12783.

[14] Ren X, Zhang X, He Q, et al. Prevalence of sarcopenia in Chinese community-dwelling elderly: a systematic review[J]. BMC Public Health, 2022,22(1):1702.DOI:10.1186/s12889-022-13909-z.

[15] Xiao P, Cui A, Hsu C, et al. Global, regional prevalence, and risk factors of osteoporosis according to the World Health Organization diagnostic criteria: a systematic review and meta-analysis[J]. Osteoporos Int, 2022,33(10):2137-2153.DOI:10.1007/s00198-022-06454-3.

[16] Almohaisen N, Gittins M, Todd C, et al. Prevalence of Undernutrition, Frailty and Sarcopenia in Community-Dwelling People Aged 50 Years and Above: Systematic Review and Meta-Analysis[J]. Nutrients, 2022,14(8):1537.DOI:10.3390/nu14081537.

[17] Zang C, Zhang H, Xu J, et al. High-throughput target trial emulation for Alzheimer’s disease drug repurposing with real-world data[J]. Nature Communications, 2023,14(1):8180.DOI:10.1038/s41467-023-43929-1.

[18] Dash R, Yadav M, Biswal J, et al. Drug repurposing a compelling cancer strategy with bottomless opportunities: Recent advancements in computational methods and molecular mechanisms[J]. Indian J Pharmacol, 2023,55(5):322-331.DOI:10.4103/ijp.ijp_626_22.

[19] Bernardo L, Lomagno A, Mauri P L, et al. Integration of Omics Data and Network Models to Unveil Negative Aspects of SARS-CoV-2, from Pathogenic Mechanisms to Drug Repurposing[J]. Biology, 2023,12(9):1196.DOI:10.3390/biology12091196.

[20] Guo D, Lv J, Chen X, et al. Study of miRNA interactome in active rheumatoid arthritis patients reveals key pathogenic roles of dysbiosis in the infection–immune network[J]. Rheumatology, 2021,60(3):1512-1522.DOI:10.1093/rheumatology/keaa369.

[21] Chen X, Liu G, Wang S, et al. Machine learning analysis of gene expression profile reveals a novel diagnostic signature for osteoporosis[J]. J Orthop Surg Res, 2021,16(1):189.DOI:10.1186/s13018-021-02329-1.

[22] Liu Y, Shen H, Greenbaum J, et al. Gene Expression and RNA Splicing Imputation Identifies Novel Candidate Genes  Associated with Osteoporosis[J]. J Clin Endocrinol Metab, 2020,105(12):e4742-e4757.DOI:10.1210/clinem/dgaa572.

[23] Zhou X, Zhao L, Zhang Z, et al. Identification of shared gene signatures and pathways for diagnosing osteoporosis with sarcopenia through integrated bioinformatics analysis and machine learning[J]. BMC Musculoskeletal Disorders, 2024,25(1):435.DOI:10.1186/s12891-024-07555-2.

[24] Szklarczyk D, Kirsch R, Koutrouli M, et al. The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest[J]. Nucleic Acids Research, 2023,51(D1):D638-D646.DOI:10.1093/nar/gkac1000.

[25] Kohl M, Wiese S, Warscheid B. Cytoscape: software for visualization and analysis of biological networks[J]. Methods Mol Biol, 2011,696:291-303.DOI:10.1007/978-1-60761-987-1_18.

[26] Bader G D, Hogue C W V. An automated method for finding molecular complexes in large protein interaction networks[J]. BMC bioinformatics, 2003,4:2.DOI:10.1186/1471-2105-4-2.

[27] Chin C, Chen S, Wu H, et al. cytoHubba: identifying hub objects and sub-networks from complex interactome[J]. BMC systems biology, 2014,8(Suppl 4):S11.DOI:10.1186/1752-0509-8-S4-S11.

[28] Darang E, Pezeshkian Z, Mirhoseini S Z, et al. Bioinformatics and pathway enrichment analysis identified hub genes and potential biomarker for gastric cancer prognosis[J]. Frontiers in Oncology, 2023,13:1187521.DOI:10.3389/fonc.2023.1187521.

[29] Liao Y, Wang J, Jaehnig E J, et al. WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs[J]. Nucleic Acids Research, 2019,47(W1):W199-W205.DOI:10.1093/nar/gkz401.

[30] Reimand J, Kull M, Peterson H, et al. g:Profiler—a web-based toolset for functional profiling of gene lists from large-scale experiments[J]. Nucleic Acids Research, 2007,35(suppl_2):W193-W200.DOI:10.1093/nar/gkm226.

[31] Kanehisa M, Furumichi M, Tanabe M, et al. KEGG: new perspectives on genomes, pathways, diseases and drugs[J]. Nucleic Acids Research, 2017,45(D1):D353-D361.DOI:10.1093/nar/gkw1092.

[32] Dweep H, Sticht C, Pandey P, et al. miRWalk--database: prediction of possible miRNA binding sites by "walking" the genes of three genomes[J]. Journal of biomedical informatics, 2011,44(5):839-847. DOI:10.1016/j.jbi.2011.05.002.

[33] Chang L, Zhou G, Soufan O, et al. miRNet 2.0: network-based visual analytics for miRNA functional analysis and systems biology[J]. Nucleic Acids Res, 2020,48(W1):W244-W251.D OI:10.1093/nar/gkaa467.

[34] Cannon M, Stevenson J, Stahl K, et al. DGIdb 5.0: rebuilding the drug–gene interaction database for precision medicine and drug discovery platforms[J]. Nucleic Acids Research, 2024,52(D1):D1227-D1235. DOI:10.1093/nar/gkad1040.

[35] Murray P J. The JAK-STAT signaling pathway: input and output integration[J]. Journal of immunology (Baltimore, Md. : 1950), 2007,178(5):2623-2629.DOI:10.4049/jimmunol.178.5.2623.

[36] Zhou X, Zhao J, Yan T, et al. ANXA9 facilitates S100A4 and promotes breast cancer progression through modulating STAT3 pathway[J]. Cell Death Dis, 2024,15(4):260.DOI:10.1038/s41419-024-06643-4.

[37] Xie C, Zhou X, Liang C, et al. Apatinib triggers autophagic and apoptotic cell death via VEGFR2/STAT3/PD-L1 and ROS/Nrf2/p62 signaling in lung cancer[J]. Journal of Experimental & Clinical Cancer Research, 2021,40(1):266.DOI:10.1186/s13046-021-02069-4.

[38] Sims N A. The JAK1/STAT3/SOCS3 axis in bone development, physiology, and pathology[J]. Experimental & Molecular Medicine, 2020,52(8):1185-1197.DOI:10.1038/s12276-020-0445-6.

[39] Zhu Y, Wang A, Zhang S, et al. Paclitaxel-loaded ginsenoside Rg3 liposomes for drug-resistant cancer therapy by dual targeting of the tumor microenvironment and cancer cells[J]. Journal of advanced research, 2023,49:159-173.DOI:10.1016/j.jare.2022.09.007.

[40] Li Q, Zhu M, Liu X, et al. Abnormally low serum albumin levels are associated with abnormal bone mineral density and osteoporotic fractures: a retrospective studies[J]. BMC Musculoskeletal Disorders, 2024,25(1):888.DOI:10.1186/s12891-024-08021-9.

[41] Wang J, Zhang Y, Cao J, et al. The role of autophagy in bone metabolism and clinical significance[J]. Autophagy, 2023,19(9):2409-2427.DOI:10.1080/15548627.2023.2186112.

[42] Tylutka A, Walas Ł, Zembron-Lacny A. Level of IL-6, TNF, and IL-1β and age-related diseases: a systematic review and meta-analysis[J]. Frontiers in Immunology, 2024,15:1330386. DOI:10.3389/fimmu.2024.1330386.

[43] Wan B, Zhou J, Teng Y, et al. Identification of a key environment-responsive gene mediating environmental impact on postmenopausal osteoporosis[J]. Frontiers in Public Health, 2025,13:1536851. DOI:10.3389/fpubh.2025.1536851.

[44] Li Z, Xu J, Shi S, et al. Identification and validation of iron metabolism genes in osteoporosis[J]. BMC Medical Genomics, 2024,17(1):5.DOI:10.1186/s12920-023-01779-2.

[45] Henze H, Hüttner S S, Koch P, et al. Denervation alters the secretome of myofibers and thereby affects muscle stem cell lineage progression and functionality[J]. npj Regenerative Medicine, 2024,9(1):10.DOI:10.1038/s41536-024-00353-3.

[46] He H, Gu S. The PPAR-γ/SFRP5/Wnt/β-catenin signal axis regulates the dexamethasone-induced osteoporosis[J]. Cytokine, 2021,143:155488.DOI:10.1016/j.cyto.2021.155488.

[47] Yan S B, Liang H, Zhan P, et al. Stimulator of interferon genes promotes diabetic sarcopenia by targeting peroxisome proliferator activated receptors γ degradation and inhibiting fatty acid oxidation[J]. Journal of Cachexia, Sarcopenia and Muscle, 2023,14(6):2623-2641.DOI:10.1002/jcsm.13336.

[48] Yu Y, Yao P, Wang Z, et al. MiR-137 promotes TLR4/NF-κB pathway activity through targeting KDM4A, inhibits osteogenic differentiation of human bone marrow mesenchymal stem cells and aggravates osteoporosis[J]. Journal of Orthopaedic Surgery and Research, 2023,18(1):444. DOI:10.1186/s13018-023-03918-y.

[49] Wu Y, Yao X, Shi X, et al. Myeloma extracellular vesicle-derived RAGE increases inflammatory responses and myotube atrophy in multiple myeloma through activation of the TLR4/NF-κB p65 pathway[J]. Apoptosis : an international journal on programmed cell death, 2024,29(5-6):849-864.DOI:10.1007/s10495-023-01920-7.

[50] Nada H, Sivaraman A, Lu Q, et al. Perspective for Discovery of Small Molecule IL-6 Inhibitors through Study of Structure-Activity Relationships and Molecular Docking[J]. Journal of medicinal chemistry, 2023,66(7):4417-4433.DOI:10.1021/acs.jmedchem.2c01957.

[51] Aliyu M, Zohora F T, Anka A U, et al. Interleukin-6 cytokine: An overview of the immune regulation, immune dysregulation, and therapeutic approach[J]. International immunopharmacology, 2022,111:109130. DOI:10.1016/j.intimp.2022.109130.

[52] Oh K, Adnan M, Cho D. Drug Investigation to Dampen the Comorbidity of Rheumatoid Arthritis and Osteoporosis via Molecular Docking Test[J]. Current Issues in Molecular Biology, 2022,44(3):1046-1061.DOI:10.3390/cimb44030069.

[53] Becker M, Joseph S S, Garcia-Carrizo F, et al. Regulatory T cells require IL6 receptor alpha signaling to control skeletal muscle function and regeneration[J]. Cell metabolism, 2023,35(10):1736-1751.DOI:10.1016/j.cmet.2023.08.010.

[54] Xia T, Zhang M, Lei W, et al. Advances in the role of STAT3 in macrophage polarization[J]. Frontiers in immunology, 2023,14:1160719.DOI:10.3389/fimmu.2023.1160719.

[55] Chen X, Ji Z L, Chen Y Z. TTD: Therapeutic Target Database[J]. Nucleic acids research, 2002,30(1):412-415.DOI:10.1093/nar/30.1.412.

[56] Piñero J, Ramírez-Anguita J M, Saüch-Pitarch J, et al. The DisGeNET knowledge platform for disease genomics: 2019 update[J]. Nucleic acids research, 2020,48(D1):D845-D855. DOI:10.1093/nar/gkz1021.

[57] Rahnama M, Tehrani H A, Mirzaie M, et al. Identification of key genes and convergent pathways disrupted in autism spectrum disorder via comprehensive bioinformatic analysis[J]. Informatics in medicine unlocked, 2021,24:100589.DOI:10.1016/j.imu.2021.100589.

[58] Sipprell S E, Krueger Q A, Mills E L, et al. Substance P Augments Chemokine Production by Staphylococcus aureus Infected Murine Osteoclasts[J]. Inflammation, 2025.DOI:10.1007/s10753-025-02280-x.

[59] Xu Y, Yan H, Zhang X, et al. Roles of Altered Macrophages and Cytokines: Implications for Pathological Mechanisms of Postmenopausal Osteoporosis, Rheumatoid Arthritis, and Alzheimer's Disease[J]. Frontiers in endocrinology, 2022,13:876269.DOI:10.3389/fendo.2022.876269.