Investigation of transcriptome mechanism associated with osteoporosis explored by microarray analysis

Liu,Yan; Li,Ying; Liu,Xing; Wang,Chun-Sheng

doi:10.3892/etm.2019.7349

Investigation of transcriptome mechanism associated with osteoporosis explored by microarray analysis

Authors:
- Yan Liu
- Ying Li
- Xing Liu
- Chun-Sheng Wang
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Affiliations: Department of Spine Surgery, First Hospital, Jilin University, Changchun, Jilin 130021, P.R. China, Beijing Splinger Medical Research Institute, Beijing 100054, P.R. China, Department of Orthopedics, Affiliated YanTaiYeDa Hospital of Binzhou Medical College, Yantai, Shandong 264006, P.R. China
Published online on: March 6, 2019 https://doi.org/10.3892/etm.2019.7349
Pages: 3459-3464
Copyright: © Liu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Microarray data of osteoporosis (OP) were analyzed based on prediction of transcription factors (TFs) or their targets as well as influences of TFs or TF network to uncover key TFs in OP. The microarray data E-GEOD-35956 was downloaded from the GPL570 platform. Differentially expressed genes (DEGs) with logarithm of fold change (|logFC|) >2 and P-value <0.05 were identified between OP samples and normal controls. TF genes were screened from the DEGs based on ITFP, Marbach 2016, TRRUST databases. TF targets were enriched from DEGs using Fisher's exact test. TF targets were selected based on their impact factors. TF targets were chosen from TF network analysis. Finally, key TFs were identified by based on TFs coverage. A total of 300 DEGs were obtained. There were no TF genes screened from the DEGs. In total 165, 87 and 178 TF targets were screened from DEGs respectively based on Fisher's exact test, influence of TFs or TF network analysis. According to the optimal TF set with TFs having maximum coverage of DEGs, 178 TF targets was the most. Thus, the optimal sets of TFs were FOXO1, KLF16, RXRA, RARA, HNF4A, CEBPB, ESR1, SOX8, ZNF219, and SP1. Altogether, these results suggested identified crucial TFs in OP might play a significant role in OP development, showing these key TFs probably would aid in unveiling the underlying molecular mechanisms and may be therapeutic targets, diagnostic or prognostic biomarkers for OP.

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