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Current Bioinformatics

Editor-in-Chief

ISSN (Print): 1574-8936
ISSN (Online): 2212-392X

Research Article

Identification of Critical Functional Modules and Signaling Pathways in Osteoporosis

Author(s): Xiaowei Jiang*, Pu Ying*, Yingchao Shen, Yiming Miu, Wenbin Kong, Tong Lu and Qiang Wang

Volume 16, Issue 1, 2021

Published on: 05 July, 2020

Page: [90 - 97] Pages: 8

DOI: 10.2174/1574893615999200706002411

Price: $65

Abstract

Background: Osteoporosis is the most common bone metabolic disease. Abnormal osteoclast formation and resorption play a fundamental role in osteoporosis pathogenesis. Recent researches have greatly broadened our understanding of molecular mechanisms of osteoporosis. However, the molecular mechanisms leading to osteoporosis are still not entirely clear.

Objective: The purpose of this work is to study the critical regulatory genes, functional modules, and signaling pathways.

Methods: Differential expression analysis, network topology-based analysis, and overrepresentation enrichment analysis (ORA) were used to identify differentially expressed genes (DEGs), gene subnetworks, and signaling pathways related to osteoporosis, respectively.

Results: Differential expression analysis identified DEGs, such as POGLUT1, DAPK3 and NFKBIA, associated with osteoclastogenesis, which highlighted Notch, apoptosis and NF-kB signaling pathways. Network topology-based analysis identified the upregulated subnetwork characterized by EXOSC8 and DIS3L from the RNA exosome complex, and the downregulated subnetwork composed of histone deacetylases and the cofactors, MORF4L1 and JDP2. Furthermore, the overrepresentation enrichment analysis highlighted that corticotrophin-releasing hormone signaling pathway might affect osteoclastogenesis through its component NR4A1, and suppressing osteoclast differentiation and osteoclast bone resorption with urocortin (UCN).

Conclusion: Our systematic analysis not only discovered novel molecular mechanisms but also proposed potential drug targets for osteoporosis.

Keywords: Osteoporosis, critical regulatory genes, functional modules, signaling pathways, osteoclastogenesis, hormone.

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[1]
Eastell R, O’Neill TW, Hofbauer LC, et al. Postmenopausal osteoporosis. Nat Rev Dis Primers 2016; 2: 16069.
[http://dx.doi.org/10.1038/nrdp.2016.69] [PMID: 27681935]
[2]
Abrahamsen B, Vestergaard P, Rud B, et al. Ten-year absolute risk of osteoporotic fractures according to BMD T score at menopause: the Danish Osteoporosis Prevention Study. J Bone Mineral Res 2006; 21(5): 796-800.
[3]
Kanis JA, Johansson H, Oden A, et al. A family history of fracture and fracture risk: a meta-analysis. Bone 2004; 35(5): 1029-37.
[http://dx.doi.org/10.1016/j.bone.2004.06.017] [PMID: 15542027]
[4]
Kanis JA, Johnell O, De Laet C, et al. A meta-analysis of previous fracture and subsequent fracture risk. Bone 2004; 35(2): 375-82.
[http://dx.doi.org/10.1016/j.bone.2004.03.024] [PMID: 15268886]
[5]
Kanis JA, Johansson H, Oden A, et al. A meta-analysis of prior corticosteroid use and fracture risk. J Bone Mineral Res 2004; 19(6): 893-9.
[http://dx.doi.org/10.1359/JBMR.040134]
[6]
Kanis JA, Johansson H, Johnell O, et al. Alcohol intake as a risk factor for fracture. Osteoporosis 2005; 16(7): 737-42.
[http://dx.doi.org/10.1007/s00198-004-1734-y]
[7]
Kanis JA, Johnell O, Oden A, et al. Smoking and fracture risk: a meta-analysis. Osteoporosis Int 2005; 16(2): 155-62.
[http://dx.doi.org/10.1007/s00198-004-1640-3]
[8]
Cole RE. Improving clinical decisions for women at risk of osteoporosis: dual-femur bone mineral density testing. J Am Osteopath Assoc 2008; 108(6): 289-95.
[PMID: 18587077]
[9]
Johnell O, Kanis JA. An estimate of the worldwide prevalence and disability associated with osteoporotic fractures. Osteoporosis Int 2006; 17(12): 1726-33.
[http://dx.doi.org/10.1007/s00198-006-0172-4]
[10]
Ikeda K, Takeshita S. Factors and mechanisms involved in the coupling from bone resorption to formation: how osteoclasts talk to osteoblasts. J Bone Metab 2014; 21(3): 163-7.
[http://dx.doi.org/10.11005/jbm.2014.21.3.163] [PMID: 25247154]
[11]
Matsuoka K, Park KA, Ito M, Ikeda K, Takeshita S. Osteoclast-derived complement component 3a stimulates osteoblast differentiation. J Bone Miner Res 2014; 29(7): 1522-30.
[http://dx.doi.org/10.1002/jbmr.2187] [PMID: 24470120]
[12]
Terpos E, Voskaridou E. Interactions between osteoclasts, osteoblasts and immune cells: implications for the pathogenesis of bone loss in thalassemia. Pediatr Endocrinol Rev 2008; 6(Suppl. 1): 94-106.
[PMID: 19337162]
[13]
Chen XF, Zhu DL, Yang M, et al. An osteoporosis risk SNP at 1p36.12 acts as an allele-specific enhancer to modulate LINC00339 expression via long-range loop formation. Am J Hum Genet 2018; 102(5): 776-93.
[http://dx.doi.org/10.1016/j.ajhg.2018.03.001] [PMID: 29706346]
[14]
Reppe S, Lien TG, Hsu YH, et al. Distinct DNA methylation profiles in bone and blood of osteoporotic and healthy postmenopausal women. Epigenetics 2017; 12(8): 674-87.
[http://dx.doi.org/10.1080/15592294.2017.1345832] [PMID: 28650214]
[15]
Zhou Y, Zhu W, Zhang L, et al. Transcriptomic data identified key transcription factors for osteoporosis in caucasian women. Calcif Tissue Int 2018; 103(6): 581-8.
[http://dx.doi.org/10.1007/s00223-018-0457-6] [PMID: 30056508]
[16]
Zhou Y, Xu C, Zhu W, et al. Long noncoding RNA analyses for osteoporosis risk in caucasian women. Calcif Tissue Int 2019; 105(2): 183-92.
[http://dx.doi.org/10.1007/s00223-019-00555-8] [PMID: 31073748]
[17]
Zhou Y, Gao Y, Xu C, Shen H, Tian Q, Deng HW. A novel approach for correction of crosstalk effects in pathway analysis and its application in osteoporosis research. Sci Rep 2018; 8(1): 668.
[http://dx.doi.org/10.1038/s41598-018-19196-2] [PMID: 29330445]
[18]
Liu YZ, Zhou Y, Zhang L, et al. Attenuated monocyte apoptosis, a new mechanism for osteoporosis suggested by a transcriptome-wide expression study of monocytes. PLoS One 2015; 10(2): e0116792.
[http://dx.doi.org/10.1371/journal.pone.0116792] [PMID: 25659073]
[19]
Irizarry RA, Bolstad BM, Collin F, Cope LM, Hobbs B, Speed TP. Summaries of affymetrix genechip probe level data. Nucleic Acids Res 2003; 31(4): e15.
[http://dx.doi.org/10.1093/nar/gng015] [PMID: 12582260]
[20]
Carvalho BS, Irizarry RA. A framework for oligonucleotide microarray preprocessing. Bioinformatics 2010; 26(19): 2363-7.
[http://dx.doi.org/10.1093/bioinformatics/btq431] [PMID: 20688976]
[21]
Wang J, Vasaikar S, Shi Z, Greer M, Zhang B. WebGestalt 2017: a more comprehensive, powerful, flexible and interactive gene set enrichment analysis toolkit. Nucleic Acids Res 2017; 45(W1): W130-7.
[http://dx.doi.org/10.1093/nar/gkx356] [PMID: 28472511]
[22]
Ashburner M, Ball CA, Blake JA, et al. Gene ontology: tool for the unification of biology. the gene ontology consortium. Nat Genet 2000; 25(1): 25-9.
[http://dx.doi.org/10.1038/75556] [PMID: 10802651]
[23]
Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 2005; 102(43): 15545-50.
[http://dx.doi.org/10.1073/pnas.0506580102] [PMID: 16199517]
[24]
Shomali T, Kamalpour M, Fazeli M, Rafati A. Expression of HCA2 receptors in femoral epiphysis and metaphysis of rats with dexamethasone-induced osteoporosis. Int J Mol Cell Med 2016; 5(2): 106-13.
[PMID: 27478807]
[25]
Servián-Morilla E, Takeuchi H, Lee TV, et al. A POGLUT1 mutation causes a muscular dystrophy with reduced Notch signaling and satellite cell loss. EMBO Mol Med 2016; 8(11): 1289-309.
[http://dx.doi.org/10.15252/emmm.201505815] [PMID: 27807076]
[26]
Ashley JW, Ahn J, Hankenson KD. Notch signaling promotes osteoclast maturation and resorptive activity. J Cell Biochem 2015; 116(11): 2598-609.
[http://dx.doi.org/10.1002/jcb.25205] [PMID: 25914241]
[27]
Kawai T, Matsumoto M, Takeda K, Sanjo H, Akira S. ZIP kinase, a novel serine/threonine kinase which mediates apoptosis. Mol Cell Biol 1998; 18(3): 1642-51.
[http://dx.doi.org/10.1128/MCB.18.3.1642] [PMID: 9488481]
[28]
Soysa NS, Alles N. NF-kappaB functions in osteoclasts. Biochem Biophys Res Commun 2009; 378(1): 1-5.
[http://dx.doi.org/10.1016/j.bbrc.2008.10.146] [PMID: 18992710]
[29]
Abu-Amer Y. NF-κB signaling and bone resorption. Osteoporos Int 2013; 24(9): 2377-86.
[http://dx.doi.org/10.1007/s00198-013-2313-x] [PMID: 23468073]
[30]
Boyce BF, Xiu Y, Li J, Xing L, Yao Z. NF-κB-mediated regulation of osteoclastogenesis. Endocrinol Metab 2015; 30(1): 35-44.
[http://dx.doi.org/10.3803/EnM.2015.30.1.35] [PMID: 25827455]
[31]
Bradley EW, Carpio LR, van Wijnen AJ, McGee-Lawrence ME, Westendorf JJ. Histone deacetylases in bone development and skeletal disorders. Physiol Rev 2015; 95(4): 1359-81.
[http://dx.doi.org/10.1152/physrev.00004.2015] [PMID: 26378079]
[32]
Scholtysek C, Ipseiz N, Böhm C, et al. NR4A1 regulates motility of osteoclast precursors and serves as target for the modulation of systemic bone turnover. J Bone Miner Res 2018; 33(11): 2035-47.
[http://dx.doi.org/10.1002/jbmr.3533] [PMID: 29949664]
[33]
Combs CE, Fuller K, Kumar H, et al. Urocortin is a novel regulator of osteoclast differentiation and function through inhibition of a canonical transient receptor potential 1-like cation channel. J Endocrinol 2012; 212(2): 187-97.
[http://dx.doi.org/10.1530/JOE-11-0254] [PMID: 22083217]
[34]
Huang CC, Narayanan R, Alapati S, Ravindran S. Exosomes as biomimetic tools for stem cell differentiation: Applications in dental pulp tissue regeneration. Biomaterials 2016; 111: 103-15.
[http://dx.doi.org/10.1016/j.biomaterials.2016.09.029] [PMID: 27728810]
[35]
Zhu Y, Jia Y, Wang Y, Xu J, Chai Y. Impaired bone regenerative effect of exosomes derived from bone marrow mesenchymal stem cells in type 1 diabetes. Stem Cells Transl Med 2019; 8(6): 593-605.
[http://dx.doi.org/10.1002/sctm.18-0199] [PMID: 30806487]
[36]
Behera J, Tyagi N. Exosomes: mediators of bone diseases, protection, and therapeutics potential. Oncoscience 2018; 5(5-6): 181-95.
[http://dx.doi.org/10.18632/oncoscience.421] [PMID: 30035185]
[37]
Li L, Wang XQ, Liu XT, Guo R, Zhang RD. Integrative analysis reveals key mRNAs and lncRNAs in monocytes of osteoporotic patients. Math Biosci Eng 2019; 16(5): 5947-71.
[http://dx.doi.org/10.3934/mbe.2019298] [PMID: 31499747]

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