Dataset Information

Circulating miRNAs are associated with successful bone regeneration

ABSTRACT: Introduction: Bone healing is a well-orchestrated process involving various bone cells and signaling pathways, where disruptions can result in delayed or incomplete healing. MicroRNAs (miRNAs) are small non-coding RNAs capable of influencing various cellular processes, including bone remodeling. Due to their biological relevance and stable presence in biofluids, miRNAs may serve as candidates for diagnosis and prognosis of delayed bone healing. The aim of this study was to investigate changes in miRNAs circulating in the blood during the healing of rat calvaria defects as biomarkers of successful bone regeneration. Methods: Standardized calvaria defects were created in 36 Wistar rats with a trephine drill and treated with collagen hydroxyapatite (CHA) scaffolds. The treatment groups included CHA scaffolds only, CHA scaffolds containing a plasmid coding for bone morphogenetic protein 2 (BMP2) and miR-590-5p, CHA scaffolds containing mesenchymal stromal cell-derived extracellular vesicles, and empty defects as a control group. After 1, 4 and 8 weeks of healing, the animals were evaluated by microcomputed tomography (microCT), as well as subjected to histological analyses. Blood was sampled from the tail vein prior to surgeries and after 1, 4, and 8 weeks of healing. miRNAs circulating in the plasma were determined using next generation sequencing. Results: Variability of bone regeneration within the four groups was unexpectedly high and did not result in significant differences between the groups, as indicated by the microCT and histological analyses of the newly formed bone tissue. However, irrespective of the treatment group and regenerative activity, we identified miRNAs with distinct expression patterns of up- and downregulation at different time points. Furthermore, rats with high and low regenerative activity were characterized by distinct circulating miRNA profiles. miR-133-3p was identified as the top up-regulated miRNA and miR-375-3p was identified as the top down- regulated miRNA in animals exhibiting good regeneration over all time points evaluated. Conclusion: Our study indicates that regardless of the treatment group, success or lack of bone regeneration is associated with a distinct expression pattern of circulating microRNAs. While for some of these microRNAs functional association with skeletal regeneration has previously been reported, further research is needed to evaluate whether their levels in the blood can be used as predictive factors of successful bone regeneration. Keywords: gene-activated scaffold; osteogenesis; bone regeneration, biomarkers, circulating microRNAs

ORGANISM(S): Rattus norvegicus

PROVIDER: GSE279239 | GEO | 2025/03/27

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Children less than 2 years of age are capable of healing large calvarial defects, whereas adults have been found to lack this endogenous ability. In this study, we used microarray analysis to compare genomewide expression patterns during active regeneration after injury with calvaria in skeletally immature and mature mice. Parietal bone defects were created in 6-day-old (juvenile) and 60-day-old (adult) mice using a 4-mm trephine bit (n = 20 mice per age group). The calvarial disc was removed, leaving the underlying dura mater intact. Two weeks after injury, the region of regeneration with the underlying dura mater was harvested, and RNA was extracted for microarray analysis. The 25 most differentially upregulated genes in juvenile regenerates compared with adults were listed, as well as selected bone-related genes. In addition, QRT-PCR confirmation of specific genes was performed for validation. Juvenile regenerates expressed significantly greater amounts of BMP-2, -4, -7, as well as FGF-2 and its receptor FGFR-1. Various other growth factors were also noted to be upregulated, including IGF-2 and Ptn. This corresponded with the increased expression of markers for osteogenic differentiation of Sparc and Oc. Markers of osteoclast activity, Acp5, Ctsk, and Mmp2, were noted to be greater in juvenile regenerates compared with adults. The observation of Mmp14 upregulation, however, highlights the importance of balanced osteoclast-mediated bone resorption for ultimate healing. The 2 most differentially regulated genes, transthyretin (Ttr) and prostaglandin D2 synthase (Ptgds), highlight the potential role of retinoic acid signaling and the prostaglandin axis on skeletal regeneration. These findings underscore the multitude of biomolecular mechanisms at play, allowing juvenile calvaria to heal after injury. The identification of various growth factors and cytokines involved also suggests novel therapeutic strategies for tissue-engineering purposes. Set of arrays that are part of repeated experiments Elapsed Time: Calvarial regeneration in 6 day old vs 60 day old mice Biological Replicate

Project description:Proctor2017 - Identifying microRNA for muscle regeneration during ageing (Mir1_in_muscle) This model is described in the article: Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing Carole J. Proctor & Katarzyna Goljanek-Whysall Nature Scientific Reports Abstract: MicroRNAs (miRNAs) regulate gene expression through interactions with target sites within mRNAs, leading to enhanced degradation of the mRNA or inhibition of translation. Skeletal muscle expresses many different miRNAs with important roles in adulthood myogenesis (regeneration) and myofibre hypertrophy and atrophy, processes associated with muscle ageing. However, the large number of miRNAs and their targets mean that a complex network of pathways exists, making it difficult to predict the effect of selected miRNAs on age-related muscle wasting. Computational modelling has the potential to aid this process as it is possible to combine models of individual miRNA:target interactions to form an integrated network. As yet, no models of these interactions in muscle exist. We created the first model of miRNA:target interactions in myogenesis based on experimental evidence of individual miRNAs which were next validated and used to make testable predictions. Our model confirms that miRNAs regulate key interactions during myogenesis and can act by promoting the switch between quiescent/proliferating/differentiating myoblasts and by maintaining the differentiation process. We propose that a threshold level of miR-1 acts in the initial switch to differentiation, with miR-181 keeping the switch on and miR-378 maintaining the differentiation and miR-143 inhibiting myogenesis. This model is hosted on BioModels Database and identified by: MODEL1704110000. To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Proctor2017 - Identifying microRNA for muscle regeneration during ageing (Mir181_in_muscle) This model is described in the article: Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing Carole J. Proctor & Katarzyna Goljanek-Whysall Scientific Reports Abstract: MicroRNAs (miRNAs) regulate gene expression through interactions with target sites within mRNAs, leading to enhanced degradation of the mRNA or inhibition of translation. Skeletal muscle expresses many different miRNAs with important roles in adulthood myogenesis (regeneration) and myofibre hypertrophy and atrophy, processes associated with muscle ageing. However, the large number of miRNAs and their targets mean that a complex network of pathways exists, making it difficult to predict the effect of selected miRNAs on age-related muscle wasting. Computational modelling has the potential to aid this process as it is possible to combine models of individual miRNA:target interactions to form an integrated network. As yet, no models of these interactions in muscle exist. We created the first model of miRNA:target interactions in myogenesis based on experimental evidence of individual miRNAs which were next validated and used to make testable predictions. Our model confirms that miRNAs regulate key interactions during myogenesis and can act by promoting the switch between quiescent/proliferating/differentiating myoblasts and by maintaining the differentiation process. We propose that a threshold level of miR-1 acts in the initial switch to differentiation, with miR-181 keeping the switch on and miR-378 maintaining the differentiation and miR-143 inhibiting myogenesis. This model is hosted on BioModels Database and identified by: MODEL1704110001. To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Proctor2017 - Identifying microRNA for muscle regeneration during ageing (Mir378_in_muscle) This model is described in the article: Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing Carole J. Proctor & Katarzyna Goljanek-Whysall Scientific Reports Abstract: MicroRNAs (miRNAs) regulate gene expression through interactions with target sites within mRNAs, leading to enhanced degradation of the mRNA or inhibition of translation. Skeletal muscle expresses many different miRNAs with important roles in adulthood myogenesis (regeneration) and myofibre hypertrophy and atrophy, processes associated with muscle ageing. However, the large number of miRNAs and their targets mean that a complex network of pathways exists, making it difficult to predict the effect of selected miRNAs on age-related muscle wasting. Computational modelling has the potential to aid this process as it is possible to combine models of individual miRNA:target interactions to form an integrated network. As yet, no models of these interactions in muscle exist. We created the first model of miRNA:target interactions in myogenesis based on experimental evidence of individual miRNAs which were next validated and used to make testable predictions. Our model confirms that miRNAs regulate key interactions during myogenesis and can act by promoting the switch between quiescent/proliferating/differentiating myoblasts and by maintaining the differentiation process. We propose that a threshold level of miR-1 acts in the initial switch to differentiation, with miR-181 keeping the switch on and miR-378 maintaining the differentiation and miR-143 inhibiting myogenesis. This model is hosted on BioModels Database and identified by: MODEL1704110002. To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Proctor2017 - Identifying microRNA for muscle regeneration during ageing (Mir143_in_muscle) This model is described in the article: Using computer simulation models to investigate the most promising microRNAs to improve muscle regeneration during ageing Carole J. Proctor & Katarzyna Goljanek-Whysall Scientific Reports Abstract: MicroRNAs (miRNAs) regulate gene expression through interactions with target sites within mRNAs, leading to enhanced degradation of the mRNA or inhibition of translation. Skeletal muscle expresses many different miRNAs with important roles in adulthood myogenesis (regeneration) and myofibre hypertrophy and atrophy, processes associated with muscle ageing. However, the large number of miRNAs and their targets mean that a complex network of pathways exists, making it difficult to predict the effect of selected miRNAs on age-related muscle wasting. Computational modelling has the potential to aid this process as it is possible to combine models of individual miRNA:target interactions to form an integrated network. As yet, no models of these interactions in muscle exist. We created the first model of miRNA:target interactions in myogenesis based on experimental evidence of individual miRNAs which were next validated and used to make testable predictions. Our model confirms that miRNAs regulate key interactions during myogenesis and can act by promoting the switch between quiescent/proliferating/differentiating myoblasts and by maintaining the differentiation process. We propose that a threshold level of miR-1 acts in the initial switch to differentiation, with miR-181 keeping the switch on and miR-378 maintaining the differentiation and miR-143 inhibiting myogenesis. This model is hosted on BioModels Database and identified by: MODEL1704110003. To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Dataset Information

Circulating miRNAs are associated with successful bone regeneration

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets