Sequencing identifies a distinct signature of circulating microRNAs in early radiographic knee osteoarthritis
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE151341 | GEO | 2020/10/07
REPOSITORIES: GEO
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Project description:OBJECTIVE: Our objective was to sequence the plasma miRNome from 56 patients with lumbar spinal stenosis (LSS) to determine whether miRNA signatures at time of surgery predicted pain responses one year later. MicroRNA libraries were prepared using the QIAseq miRNA Library Kit and sequenced on the Illumina NextSeq550. Counts were produced for microRNAs captured in miRBase
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Project description:Sequencing identifies a distinct signature of circulating microRNAs in early radiographic knee osteoarthritis
| PRJNA635567 | ENA
Project description:The set of expressed microRNAs in a given cell type, or “miRNome”, can be explored under many different aspects. Many studies report modulations of the miRNome in a wide variety of cancers. Papillary thyroid cancer is the most prevalent type of endocrine cancer. The presence of nodal metastases increases the risk of recurrence and mortality. In our study, we performed microRNA deep sequencing (miRSeq) of 3 PTC, their matching normal tissues and nodal metastases and designed a new bioinformatic framework to analyze variations of the different aspects of the miRNome: expression profile, isomiRs and non-templated additions distributions, mutation or A-to-I RNA-editing. Furthermore, we validated our results using qRT-PCR on independent samples from 14 patients and using the collection of miRSeq data from The Cancer Genome Atlas (up to 495 miRseq of PTC). We gave a particular attention to cell content and contamination. We showed that microRNA expression profiles of thyrocytes are altered during tumorigenesis. These alterations involve known up regulations of microRNAs such as miR-146b-5p or miR-22-3p but also down regulations such as miR-7-5p, miR-7-2-5p, miR-1179 or miR-204-5p. Furthermore, some expression modulations were increased following the nodal metastatic process such as miR-7-2-3p or miR-138-1-3p. However, we did not find variations in the other aspects of the miRNome analyzed. We used our bioinformatic frameworks on the largest PTC miRSeq data collection available, to our knowledge. It allowed us, in one study on the different aspects of the miRNome, to find modulated microRNAs that could act as biomarkers of PTC.
2015-12-01 | GSE57780 | GEO
Project description:Proctor2017- Role of microRNAs in
osteoarthritis (Negative Feedback By MicroRNA)
This model is described in the article:
Computer simulation models
as a tool to investigate the role of microRNAs in
osteoarthritis.
Proctor CJ, Smith GR.
PLoS ONE 2017; 12(11): e0187568
Abstract:
The aim of this study was to show how computational models
can be used to increase our understanding of the role of
microRNAs in osteoarthritis (OA) using miR-140 as an example.
Bioinformatics analysis and experimental results from the
literature were used to create and calibrate models of gene
regulatory networks in OA involving miR-140 along with key
regulators such as NF-?B, SMAD3, and RUNX2. The individual
models were created with the modelling standard, Systems
Biology Markup Language, and integrated to examine the overall
effect of miR-140 on cartilage homeostasis. Down-regulation of
miR-140 may have either detrimental or protective effects for
cartilage, indicating that the role of miR-140 is complex.
Studies of individual networks in isolation may therefore lead
to different conclusions. This indicated the need to combine
the five chosen individual networks involving miR-140 into an
integrated model. This model suggests that the overall effect
of miR-140 is to change the response to an IL-1 stimulus from a
prolonged increase in matrix degrading enzymes to a pulse-like
response so that cartilage degradation is temporary. Our
current model can easily be modified and extended as more
experimental data become available about the role of miR-140 in
OA. In addition, networks of other microRNAs that are important
in OA could be incorporated. A fully integrated model could not
only aid our understanding of the mechanisms of microRNAs in
ageing cartilage but could also provide a useful tool to
investigate the effect of potential interventions to prevent
cartilage loss.
This model is hosted on
BioModels Database
and identified by:
MODEL1610100001.
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.
2019-11-14 | BIOMD0000000864 | BioModels
Project description:Proctor2017- Role of microRNAs in
osteoarthritis (Positive Feedforward Incoherent By MicroRNA)
This model is described in the article:
Computer simulation models
as a tool to investigate the role of microRNAs in
osteoarthritis.
Proctor CJ, Smith GR.
PLoS ONE 2017; 12(11): e0187568
Abstract:
The aim of this study was to show how computational models
can be used to increase our understanding of the role of
microRNAs in osteoarthritis (OA) using miR-140 as an example.
Bioinformatics analysis and experimental results from the
literature were used to create and calibrate models of gene
regulatory networks in OA involving miR-140 along with key
regulators such as NF-?B, SMAD3, and RUNX2. The individual
models were created with the modelling standard, Systems
Biology Markup Language, and integrated to examine the overall
effect of miR-140 on cartilage homeostasis. Down-regulation of
miR-140 may have either detrimental or protective effects for
cartilage, indicating that the role of miR-140 is complex.
Studies of individual networks in isolation may therefore lead
to different conclusions. This indicated the need to combine
the five chosen individual networks involving miR-140 into an
integrated model. This model suggests that the overall effect
of miR-140 is to change the response to an IL-1 stimulus from a
prolonged increase in matrix degrading enzymes to a pulse-like
response so that cartilage degradation is temporary. Our
current model can easily be modified and extended as more
experimental data become available about the role of miR-140 in
OA. In addition, networks of other microRNAs that are important
in OA could be incorporated. A fully integrated model could not
only aid our understanding of the mechanisms of microRNAs in
ageing cartilage but could also provide a useful tool to
investigate the effect of potential interventions to prevent
cartilage loss.
This model is hosted on
BioModels Database
and identified by:
MODEL1610100004.
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.
2019-11-14 | BIOMD0000000860 | BioModels
Project description:Proctor2017- Role of microRNAs in
osteoarthritis (Negative Feedback By MicroRNA with Delay)
This model is described in the article:
Computer simulation models
as a tool to investigate the role of microRNAs in
osteoarthritis.
Proctor CJ, Smith GR.
PLoS ONE 2017; 12(11): e0187568
Abstract:
The aim of this study was to show how computational models
can be used to increase our understanding of the role of
microRNAs in osteoarthritis (OA) using miR-140 as an example.
Bioinformatics analysis and experimental results from the
literature were used to create and calibrate models of gene
regulatory networks in OA involving miR-140 along with key
regulators such as NF-?B, SMAD3, and RUNX2. The individual
models were created with the modelling standard, Systems
Biology Markup Language, and integrated to examine the overall
effect of miR-140 on cartilage homeostasis. Down-regulation of
miR-140 may have either detrimental or protective effects for
cartilage, indicating that the role of miR-140 is complex.
Studies of individual networks in isolation may therefore lead
to different conclusions. This indicated the need to combine
the five chosen individual networks involving miR-140 into an
integrated model. This model suggests that the overall effect
of miR-140 is to change the response to an IL-1 stimulus from a
prolonged increase in matrix degrading enzymes to a pulse-like
response so that cartilage degradation is temporary. Our
current model can easily be modified and extended as more
experimental data become available about the role of miR-140 in
OA. In addition, networks of other microRNAs that are important
in OA could be incorporated. A fully integrated model could not
only aid our understanding of the mechanisms of microRNAs in
ageing cartilage but could also provide a useful tool to
investigate the effect of potential interventions to prevent
cartilage loss.
This model is hosted on
BioModels Database
and identified by:
MODEL1610100002.
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.
| MODEL1610100002 | BioModels