Open Access

Time-series expression profile analysis of fracture healing in young and old mice

  • Authors:
    • Chun Yuan
    • Jinfang Cai
  • View Affiliations

  • Published online on: August 9, 2017     https://doi.org/10.3892/mmr.2017.7198
  • Pages: 4529-4536
  • Copyright: © Yuan et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Bone fracture healing is a complex process, which is associated with several factors, including age and osteoporosis. Certain genes and biological processes that may contribute to fracture healing, have been identified following developments in systems biology and molecular biology technologies, which may benefit the treatment of bone fractures. The present study identified key genes, which may be important in fracture healing through bioinformatics analysis of gene microarray datasets from the Gene Expression Omnibus. Gene clusters, which were consistently up/downregulated through time following a fracture in young (6‑week‑old) mice and old (8‑month‑old retired breeders) mice were obtained via soft clustering of differentially expressed genes (DEGs) between samples at 1 and 3 days, 1 and 5 days, and 3 and 5 days post‑fracture in the two age groups, based on the Mfuzz package of R. Functional enrichment analysis of gene clusters using the Database for Annotation, Visualization and Integrated Discovery indicated that biological processes and pathways, including those associated with bone development, skeletal system development, amino sugar and nucleotide sugar metabolism, were significantly enriched in these up/downregulated genes. Of note, a total of 207 overlapped consistently upregulated genes were obtained between the two age groups, whereas no overlap was identified between the two lists of consistently downregulated genes. The overlapped genes were found to be associated with the biological processes of blood vessel development, vasculature development and skeletal system development, compared with all genes in the clusters. In addition, certain genes, including epidermal growth factor‑like domain multiple 6 (EGFL6), kazal‑type serine peptidase inhibitor domain 1 (KAZALD1), olfactomedin 2B (OLFM2B), collagen type III α1 (COL3A1), collagen type II α1 (COL2A1), von Willebrand factor A domain‑containing 1 (VWA1), elastin microfibril interfacer 1 (EMILIN1) and aggrecan (ACAN), of the extracellular matrix organization, a process performed at the cellular level and resulting in the assembly and arrangement of constituent parts, were confirmed to be associated with fracture healing via reverse transcription‑quantitative polymerase chain reaction analysis. The present study identified certain genes and biological processes/pathways, which may be associated with fracture healing and may assist in fundamental investigations and treatment in the future.

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October-2017
Volume 16 Issue 4

Print ISSN: 1791-2997
Online ISSN:1791-3004

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Spandidos Publications style
Yuan C and Cai J: Time-series expression profile analysis of fracture healing in young and old mice. Mol Med Rep 16: 4529-4536, 2017.
APA
Yuan, C., & Cai, J. (2017). Time-series expression profile analysis of fracture healing in young and old mice. Molecular Medicine Reports, 16, 4529-4536. https://doi.org/10.3892/mmr.2017.7198
MLA
Yuan, C., Cai, J."Time-series expression profile analysis of fracture healing in young and old mice". Molecular Medicine Reports 16.4 (2017): 4529-4536.
Chicago
Yuan, C., Cai, J."Time-series expression profile analysis of fracture healing in young and old mice". Molecular Medicine Reports 16, no. 4 (2017): 4529-4536. https://doi.org/10.3892/mmr.2017.7198