Age-related changes in microRNA levels in serum [mRNA]
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE51309 | GEO | 2013/10/09
SECONDARY ACCESSION(S): PRJNA222388
REPOSITORIES: GEO
Similar Datasets
Project description:microRNAs (miRNAs) are small noncoding RNAs that post-transcriptionally regulate gene expression by targeting specific mRNAs. Altered expression of circulating miRNAs have been associated with age-related diseases including cancer and cardiovascular disease. Although we and others have found an age-dependent decrease in miRNA expression in peripheral blood mononuclear cells (PBMCs), little is known about the role of circulating miRNAs in human aging. Here, we examined miRNA expression in human serum from young (mean age 30 years) and old (mean age 64 years) individuals using next generation sequencing technology and real-time quantitative PCR. Of the miRNAs that we found to be present in serum, three were significantly decreased in 20 older individuals compared to 20 younger individuals: miR-151a-5p, miR-181a-5p and miR-1248. Consistent with our data in humans, these miRNAs are also present at lower levels in the serum of elderly rhesus monkeys. In humans, miR-1248 was found to regulate the expression of mRNAs involved in inflammatory pathways and miR-181a was found to correlate negatively with the pro-inflammatory cytokines IL-6 and TNFa and to correlate positively with the anti-inflammatory cytokines TGFb and IL-10. These results suggest that circulating miRNAs may be a biological marker of aging and could also be important for regulating longevity. Identification of stable miRNA biomarkers in serum could have great potential as a noninvasive diagnostic tool as well as enhance our understanding of physiological changes that occur with age. Examination of microRNAs isolated from human serum from 11 young (mean age 30 yrs) and 11 old (mean age 64 yrs) individuals and from peripheral blood mononuclear cells from one young (30 yr) and one old (64 yr) individual.
2013-12-18 | E-GEOD-53439 | biostudies-arrayexpress
Project description:microRNAs (miRNAs) are small noncoding RNAs that post-transcriptionally regulate gene expression by targeting specific mRNAs. Altered expression of circulating miRNAs have been associated with age-related diseases including cancer and cardiovascular disease. Although we and others have found an age-dependent decrease in miRNA expression in peripheral blood mononuclear cells (PBMCs), little is known about the role of circulating miRNAs in human aging. Here, we examined miRNA expression in human serum from young (mean age 30 years) and old (mean age 64 years) individuals using next generation sequencing technology and real-time quantitative PCR. Of the miRNAs that we found to be present in serum, three were significantly decreased in 20 older individuals compared to 20 younger individuals: miR-151a-5p, miR-181a-5p and miR-1248. Consistent with our data in humans, these miRNAs are also present at lower levels in the serum of elderly rhesus monkeys. In humans, miR-1248 was found to regulate the expression of mRNAs involved in inflammatory pathways and miR-181a was found to correlate negatively with the pro-inflammatory cytokines IL-6 and TNFa and to correlate positively with the anti-inflammatory cytokines TGFb and IL-10. These results suggest that circulating miRNAs may be a biological marker of aging and could also be important for regulating longevity. Identification of stable miRNA biomarkers in serum could have great potential as a noninvasive diagnostic tool as well as enhance our understanding of physiological changes that occur with age.
2013-12-18 | GSE53439 | GEO
Project description:Objective Circulating plasma miRNAs have been increasingly studied in the field of pituitary neuroendocrine tumor (PitNET) research. Our aim was to discover circulating plasma miRNAs species associated with growth hormone (GH) secreting PitNETs and assess how the plasma levels of discovered miRNA candidates are impacted by SSA therapy and whether there is a difference in their levels between GH secreting PitNETs and other PitNET types. Methods miRNA candidates were discovered using the whole miRNA sequencing approach and differential expression analysis. Selected miRNAs were then analyzed using real-time polymerase chain reaction (qPCR). Results Whole miRNA sequencing discovered a total of 19 differentially expressed miRNAs (DEMs) in GH secreting PitNET patients' plasma 24 hours after surgery and 19 DEMs between GH secreting PitNET patients’ plasma and non-functioning (NF) PitNET patients’ plasma. Seven miRNAs were selected for further testing of which miR-625-5p, miR-503-5p miR-181a-2-3p and miR-130b-3p showed a significant downregulation in plasma after 1 month of SSA treatment. miR-181a-5p and mir-625-5p were also found to be significantly downregulated in plasma of GH secreting PitNET patients vs. NF PitNET patients. Conclusions Our study suggests that expression of plasma miRNAs miR-625-5p, miR-503-5p miR-181a-2-3p and miR-130b-3p in GH secreting PitNETs is affected by SSA treatment. Additionally, miR-625-5p and miR-181a-5p can distinguish GH secreting PitNETs from other PitNET types warranting further research on these miRNAs for treatment efficacy.
2022-02-16 | GSE196647 | GEO
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.
2017-09-26 | MODEL1704110000 | BioModels
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.
2017-09-26 | MODEL1704110001 | BioModels
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.
2017-09-26 | MODEL1704110002 | BioModels
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.
2017-09-26 | MODEL1704110003 | BioModels
Project description:Proctor2017 - Identifying microRNA for muscle
regeneration during ageing (Mirs_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:
MODEL1704110004.
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.
2017-09-26 | MODEL1704110004 | BioModels
Project description:Introduction: MicroRNAs (miRNAs) in circulation have emerged as promising biomarkers. In this study we aimed to identify a circulating miRNA signature for osteoarthritis (OA) patients. Methods: Serum samples were collected from 12 primary OA patients and 12 healthy individuals and were screened using the Agilent Human miRNA Microarray. Receiver Operating Characteristic (ROC) curves were constructed to evaluate the diagnostic performance of the deregulated miRNAs. Expression levels of selected miRNAs were validated by quantitative Real-time PCR (qRT-PCR) in all serum samples and in articular cartilage samples from OA patients (n=12) and healthy individuals (n=7). Bioinformatics analysis was used to investigate the involved pathways and target genes of the above miRNAs. Results: We identified 279 differentially expressed miRNAs in the serum of OA patients compared to healthy controls. 205 (73.5%) were up-regulated and 74 (26.5%) down-regulated. ROC analysis revealed that 77 miRNAs had area under the curve (AUC)> 0.8 and p<0.05. Bioinformatics analysis in 7 out of the 77 selected miRNAs (hsa-miR-33b-3p, hsa-miR-4284, hsa-miR-671-3p, hsa-miR-663a, hsa-miR-140-3p, hsa-miR-150-5p and hsa-miR-1233-3p) revealed that their target genes were involved in multiple signaling pathways, among which FOXO, mTOR, pI3K/akt, lipid metabolism and TGF-β. A serum miRNA signature including three down-regulated miRNAs (hsa-miR-33b-3p, hsa-miR-671-3p and hsa-miR-140-3p) were also verified by qRT-PCR in OA patients. Furthermore, we found that hsa-miR-140-3p, hsa-miR-671-3p and potentially hsa-miR-33b-3p expression levels were consistently down-regulated in articular cartilage of OA patients compared to healthy individuals. Conclusions: A global miRNA serum signature was revealed in OA patients. We identified a three- miRNA signature in peripheral serum which could be potential osteoarthritis biomarkers.
2017-10-17 | GSE105027 | GEO
Project description:In the current study we evaluated the effect of glimepiride, liraglutide on the expression of the circulating miRNAs. Univariate analyses show that treatment with glimepiride altered expression of three miRNAs in patient serum, miR-206, miR-182-5p, and miR-766-3p. Both miR-182-5p and miR-766-3p were also picked up among the top contributing miRNAs with penalized regularised logistic regressions (Lasso). The highest-ranked miRNAs with respect to Lasso coefficients were miR-3960, miR-31-5p, miR-3613-3p, and miR-378a-3p. Liraglutide treatment did not significantly influence levels of circulating miRNAs. Present study indicates that glucose-lowering drugs differently affect the expression of circulating miRNAs in serum in individuals with T2DM. More studies are required to investigate possible mechanisms by which glimepiride is affecting the expression of circulating miRNAs.
2023-01-26 | GSE223538 | GEO