4.6 Article

Brief isoflurane anaesthesia affects differential gene expression, gene ontology and gene networks in rat brain

Journal

BEHAVIOURAL BRAIN RESEARCH
Volume 317, Issue -, Pages 453-460

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.bbr.2016.09.045

Keywords

Brain; Rat; Isoflurane; Network; Gene; Anaesthesia

Funding

  1. British Journal of Anaesthesia/Royal College of Anaesthesia, via a grant from the National Institute of Academic Anaesthesia

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Much is still unknown about the mechanisms of effects of even brief anaesthesia on the brain and previous studies have simply compared differential expression profiles with and without anaesthesia. We hypothesised that network analysis, in addition to the traditional differential gene expression and ontology analysis, would enable identification of the effects of anaesthesia on interactions between genes. Rats (n = 10 per group) were randomised to anaesthesia with isoflurane in oxygen or oxygen only for 15 min, and 6 h later brains were removed. Differential gene expression and gene ontology analysis of micro-array data was performed. Standard clustering techniques and principal component analysis with Bayesian rules were used along with social network analysis methods, to quantitatively model and describe the gene networks. Anaesthesia had marked effects on genes in the brain with differential regulation of 416 probe sets by at least 2 fold. Gene ontology analysis showed 23 genes were functionally related to the anaesthesia and of these, 12 were involved with neurotransmitter release, transport and secretion. Gene network analysis revealed much greater connectivity in genes from brains from anaesthetised rats compared to controls. Other importance measures were also altered after anaesthesia; median [range] closeness centrality (shortest path) was lower in anaesthetized animals (0.07 [0-0.30]) than controls (039 [0.30-0.53], p < 0.0001) and betweenness centrality was higher (53.85 132.56-70.00]% compared to 5.93 [0-30.65]%, p < 0.0001). Simply studying the actions of individual components does not fully describe dynamic and complex systems. Network analysis allows insight into the interactions between genes after anaesthesia and suggests future targets for investigation. (C) 2016 Elsevier B.V. All rights reserved.

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