Dataset Information

Cluster Analysis of Plasma Cytokines and Neutrophil Transcriptomic Profiling of Children with Asthma in the Pediatric Intensive Care Unit

ABSTRACT: We determined whether we could identify clusters of children with critical asthma by plasma cytokine concentration. Differences in gene expression between the two clusters were analyzed using a targeted Nanostring immunology array. We performed a single-center, prospective, observational cohort study of 64 children ages 6 – 17 years admitted to a pediatric intensive care unit for an asthma attack between July 2019 to February 2021.

ORGANISM(S): Homo sapiens

PROVIDER: GSE208220 | GEO | 2022/07/15

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Critically ill intensive care unit (ICU) patients commonly develop severe muscle wasting and impaired muscle function, leading to delayed recovery, with subsequent increased morbidity and financial costs, and decrease quality of life of survivors. Acute Quadriplegic Myopathy (AQM) is one of the most common neuromuscular disorders associated with ICU-acquired muscle weakness. Although there are no available treatments for the ICU-acquired muscle weakness, it has been demonstrated that early mobilization can improve its prognosis and functional outcomes. This study aims at improving our understanding of the effects of passive mechanical loading on skeletal muscle structure and function by using a unique experimental rat ICU model allowing analyses of the temporal sequence of changes in mechanically ventilated and pharmacologically paralyzed animals at durations varying from 6 h to 14 days. Results show that passive mechanical loading alleviated the muscle wasting and the loss of force-generation associated with the ICU intervention, resulting in a doubling of the functional capacity of the loaded vs. unloaded muscles after a 2-week ICU intervention. We demonstrated that the improved maintenance of muscle structure and function is likely a consequence of a reduced oxidative stress, and a reduced loss of the molecular motor protein myosin. A complex temporal gene expression pattern, delineated by microarray analysis, was observed with loading-induced changes in transcript levels of sarcomeric proteins, muscle developmental processes, stress response, ECM/cell adhesion proteins and metabolism. Thus, the results from this study show that passive mechanical loading alleviates the severe negative consequences on muscle structure and function associated with mechanical silencing in ICU patients, strongly supporting early and intense physical therapy in immobilized ICU patients. This study aims to unravel the effects of passive mechanical loading on skeletal muscle structure and function in an experimental rat ICU model at duration varying between 6h and 14 days. A total of 23 experimental female Sprague-Dawley rats were included in this study. The experimental rats were anaesthetized, treated with the neuromuscular blocking agent (NMBA) M-NM-1-cobrotoxin, mechanically ventilated and monitored for durations varying from 6h to 4 days (n=13), from 5 to 8 days (n=4), and from 9 to 14 days (n=6). The left leg of the animal was activated for 6 hours at the shortest duration and 12 hours per day at durations 12 hours and longer throughout the experiment, using a mechanical lever arm that produced a continuous passive maximal ankle joint flexions-extensions at a speed of 13.3 cycles per minute. Muscle biopsies were obtained from gastrocnemius muscle (proximal part) immediately after euthanasia, were quickly frozen in liquid propane cooled by liquid nitrogen, and stored at -80M-BM-0C. RNA was extracted.

Project description:BACKGROUND: Evaluation of the airway transcriptome may reveal patterns of gene expression that are associated with clinical phenotypes of asthma. To define transcriptomic endotypes of asthma (TEA) we analyzed gene expression in induced sputum that correlate with phenotypes of disease. METHODS: Gene expression was measured in sputum of subjects with asthma using Affymetrix HuGene ST 1.0 microarrays. Unsupervised clustering analysis of genes in pathways selected from the Kyoto Encyclopedia of Genes and Genomes (KEGG) identified TEA clusters. Clinical characteristics were compared and logistic regression analysis of matched blood samples defined an expression profile to determine the TEA cluster assignment in a cohort of children with asthma for validation. RESULTS: Three TEA clusters were identified. TEA cluster 1 had the most subjects with a history of intubation (P = 0.05), a lower pre-bronchodilator FEV1 (P = 0.006), a higher bronchodilator response (P = 0.03), and higher exhaled nitric oxide levels (P = 0.04), compared to the other TEA clusters. TEA cluster 2, the smallest cluster had the most subjects that were hospitalized for asthma (P = 0.04). Subjects in TEA cluster 3, the largest cluster, had normal lung function, low exhaled nitric oxide levels, and lower inhaled steroid requirements. Evaluation of TEA clusters in children confirmed that TEA clusters 1 and 2 are associated with a history of intubation (P = 5.58 x 10-06) and hospitalization (P = 0.01), respectively. CONCLUSIONS: Patterns of gene expression in the sputum and blood reveal TEA clusters that are associated with severe asthma phenotypes in children and adults. Gene expression was measured in sputum of subjects with asthma using Affymetrix HuGene ST 1.0 microarrays. Unsupervised clustering analysis of genes in pathways selected from the Kyoto Encyclopedia of Genes and Genomes (KEGG) identified TEA clusters. Clinical characteristics were compared and logistic regression analysis of matched blood samples defined an expression profile to determine the TEA cluster assignment in a cohort of children with asthma for validation.

Dataset Information

Cluster Analysis of Plasma Cytokines and Neutrophil Transcriptomic Profiling of Children with Asthma in the Pediatric Intensive Care Unit

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets