Dataset Information

Circulating microRNAs as a signature predicting the occurrence of Acute Mountain Sickness before exposure to high altitude

ABSTRACT: Acute mountain sickness (AMS) is a common disabling condition in individuals experiencing high altitudes, which may progress to life-threatening high altitude cerebral edema. Today, no established biomarkers are available for prediction of AMS and Non-AMS individuals before exposure to high altitude.MicroRNAs emerge as promising sensitive and specific biomarkers for a variety of diseases. Thus, we sought to identify circulating microRNAs suitable for prediction the susceptible of AMS before exposure to high altitude. A total of 31 microRNAs were differentially expressed between AMS and Non-AMS groups, 15 up-regulated and 16 down-regulated. Up-regulation of miR-369-3p, miR-449b-3p, miR-136-3p, and miR-4791 in patients with AMS compared with Non-AMS individuals were quantitatively confirmed using qPCR (all, P < 0.001). A unique signature encompassing miR-369-3p, miR-449b-3p, and miR-136-3p discriminate AMS from Non-AMS (area under the curve 0.986, 95%CI 0.970-1.000, P < 0.001, LR+: 14.21, LR-: 0.08). This signature yielded a 92.68% sensitivity and a 93.48% specificity for AMS vs. Non-AMS.The study here, for the first time, describes a signature of three circulating microRNAs as a robust biomarker to differentiate AMS from Non-AMS individuals.

ORGANISM(S): Mus musculus Rattus norvegicus Homo sapiens

PROVIDER: GSE90500 | GEO | 2017/06/10

SECONDARY ACCESSION(S): PRJNA354917

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Background: Hypertrophic cardiomyopathy (HCM) is an autosomal dominant genetic disorder, characterized by cardiomyocyte hypertrophy, cardiomyocyte disarray and fibrosis, which has a prevalence of ~1:200-500 and predisposes individuals to sudden death and heart failure. The mechanisms through which diverse HCM-causing mutations cause cardiac dysfunction remain mostly unknown and their identification may reveal new therapeutic avenues. MicroRNAs have emerged as critical regulators of gene expression and disease phenotype in various pathologies. We explored whether miRNAs could play a role in HCM pathogenesis and offer potential therapeutic targets. Methods and Results: Using high-throughput miRNA expression profiling and qPCR analysis in two distinct mouse models of HCM, we found that miR-199a-3p expression levels are upregulated in mutant mice compared to age- and treatment-matched wild-type mice. We also found that miR-199a-3p expression is enriched in cardiac non-myocytes compared to cardiomyocytes. When we expressed miR-199a-3p mimic in cultured primary cardiac non-myocytes and analyzed the conditioned media by proteomics, we found that several ECM proteins (e.g., TSP2, FBLN3, COL11A1, LYOX) were differentially expressed. We confirmed our proteomics findings by qPCR analysis of selected mRNAs and demonstrated that miR-199a-3p mimic expression in cardiac non-myocytes drives upregulation of ECM genes including Tsp2, Fbln3, Pcoc1, Col1a1 and Col3a1. To examine the role of miR-199a-3p in vivo, we inhibited its function using lock-nucleic acid (LNA)-based inhibitors (antimiR-199a-3p) in an HCM mouse model. Our results revealed that progression of cardiac fibrosis is attenuated when miR-199a-3p function is inhibited in mild-to-moderate HCM. Finally, guided by computational target prediction algorithms, we identified mRNAs Cd151 and Itga3 as direct targets of miR-199a-3p and have shown that miR-199a-3p mimic expression negatively regulates AKT activation in cardiac non-myocytes. Conclusions: Altogether, our results suggest that miR-199a-3p may contribute to cardiac fibrosis in HCM through its actions in cardiac non-myocytes. Thus, inhibition of miR-199a-3p in mild-to-moderate HCM may offer therapeutic benefit in combination with complementary approaches that target the primary defect in cardiac myocytes.

Dataset Information

Circulating microRNAs as a signature predicting the occurrence of Acute Mountain Sickness before exposure to high altitude

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets