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      Acute Effects on the Human Peripheral Blood Transcriptome of Decompression Sickness Secondary to Scuba Diving

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          Abstract

          Decompression sickness (DCS) develops due to inert gas bubble formation in bodily tissues and in the circulation, leading to a wide range of potentially serious clinical manifestations. Its pathophysiology remains incompletely understood. In this study, we aim to explore changes in the human leukocyte transcriptome in divers with DCS compared to closely matched unaffected controls after uneventful diving. Cases ( n = 7) were divers developing the typical cutis marmorata rash after diving with a confirmed clinical diagnosis of DCS. Controls ( n = 6) were healthy divers who surfaced from a ≥25 msw dive without decompression violation or evidence of DCS. Blood was sampled at two separate time points—within 8 h of dive completion and 40–44 h later. Transcriptome analysis by RNA-Sequencing followed by bioinformatic analysis was carried out to identify differentially expressed genes and relate their function to biological pathways. In DCS cases, we identified enrichment of transcripts involved in acute inflammation, activation of innate immunity and free radical scavenging pathways, with specific upregulation of transcripts related to neutrophil function and degranulation. DCS-induced transcriptomic events were reversed at the second time point following exposure to hyperbaric oxygen. The observed changes are consistent with findings from animal models of DCS and highlight a continuum between the responses elicited by uneventful diving and diving complicated by DCS. This study sheds light on the inflammatory pathophysiology of DCS and the associated immune response. Such data may potentially be valuable in the search for novel treatments targeting this disease.

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          Most cited references 107

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          Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.

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            Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

            In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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              KEGG: kyoto encyclopedia of genes and genomes.

               M Kanehisa (2000)
              KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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                Author and article information

                Contributors
                Journal
                Front Physiol
                Front Physiol
                Front. Physiol.
                Frontiers in Physiology
                Frontiers Media S.A.
                1664-042X
                10 June 2021
                2021
                : 12
                Affiliations
                1Hyperbaric Unit, Department of Medicine, Mater Dei Hospital , Msida, Malta
                2Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU Norwegian University of Science and Technology , Trondheim, Norway
                3Faculty of Nursing and Health Sciences, Nord University , Bodø, Norway
                4Department of Clinical Pharmacology and Therapeutics, Faculty of Medicine and Surgery, University of Malta , Msida, Malta
                5Centre for Molecular Medicine and Biobanking, Faculty of Medicine and Surgery, University of Malta , Msida, Malta
                Author notes

                Edited by: Michael Bennett, University of New South Wales, Australia

                Reviewed by: Neal William Pollock, Laval University, Canada; Padhmanand Sudhakar, KU Leuven, Belgium

                *Correspondence: Nikolai Paul Pace, nikolai.p.pace@ 123456um.edu.mt

                This article was submitted to Systems Biology Archive, a section of the journal Frontiers in Physiology

                Article
                10.3389/fphys.2021.660402
                8222921
                Copyright © 2021 Magri, Eftedal, Petroni Magri, Matity, Azzopardi, Muscat and Pace.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                Page count
                Figures: 4, Tables: 4, Equations: 0, References: 98, Pages: 15, Words: 0
                Categories
                Physiology
                Original Research

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