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Identification of genes and pathways associated with multiple organ dysfunction syndrome by microarray analysis.

ABSTRACT: Multiple organ dysfunction syndrome (MODS) is characterized by the development of progressive physiological dysfunction of ?2 organs or organ systems and is responsible for the majority of the morbidity and mortality among patients in intensive care units. The aim of the present study was to investigate the potential genes and pathways associated with MODS. The microarray dataset GSE60088 was downloaded from the Gene Expression Omnibus and used to identify differentially expressed genes (DEGs) between organ tissues (lung, liver and kidney) obtained from a murine model of MODS and healthy controls. The interactions between DEGs in lungs, liver and kidneys were revealed by Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Furthermore, protein?protein interaction (PPI) data for DEGs were obtained from the Search Tool for the Retrieval of Interacting Genes and a PPI network was constructed. Additionally, DEGs that were common among the three organs were screened and transcription factors that regulated them were predicted using the iRegulon plugin. A total of 943, 267 and 227 DEGs were identified in lung, liver and kidney samples, respectively, between mice with MODS and healthy controls. In lung and liver samples, two pathways that were enriched with DEGs were identified and were common between lung and liver samples, including 'cytokine?cytokine receptor interaction' and 'Jnk?STAT signaling pathway', and examples of DEGs associated with these pathways include C?X?C motif chemokine ligand (Cxcl)1 and Cxcl10, and signal transducer and activator of transcription (Stat)1, respectively. Furthermore, two common pathways were identified in liver and kidney samples, which included 'MAPK signaling pathway' and 'p53 signaling pathway', and DEGs associated with these pathways included growth arrest and DNA damage?inducible ?. A total of 18 DEGs were common among lung, liver and kidney tissues, including CCAAT/enhancer binding protein ? (Cebpb) and olfactomedin?like 1 (Olfml1). Cebpb modulated various other DEGs, such as Cxcl1, and Olfml1 was regulated by Stat5A. These genes and pathways may serve roles in the progression of MODS and may be considered to be potential therapy targets for MODS.

SUBMITTER: Gu C

PROVIDER: S-EPMC6059685 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Identification of genes and pathways associated with multiple organ dysfunction syndrome by microarray analysis.

Gu Changwei C Qiao Wanhai W Wang Lina L Li Minmin M Song Kang K

Molecular medicine reports 20180504 1

Multiple organ dysfunction syndrome (MODS) is characterized by the development of progressive physiological dysfunction of ≥2 organs or organ systems and is responsible for the majority of the morbidity and mortality among patients in intensive care units. The aim of the present study was to investigate the potential genes and pathways associated with MODS. The microarray dataset GSE60088 was downloaded from the Gene Expression Omnibus and used to identify differentially expressed genes (DEGs) b ...[more]

PMID: 29749505

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Project description:OBJECTIVES:Patterns and outcomes of multiple organ dysfunction syndrome are unknown in critically ill children with hyperglycemia. We aimed to determine whether tight glycemic control to a lower vs. higher range influenced timing, duration, or resolution of multiple organ dysfunction syndrome as well as characterize the clinical outcomes of subgroups of multiple organ dysfunction syndrome in children enrolled in the Heart And Lung Failure-Pediatric INsulin Titration trial. DESIGN:Planned secondary analysis of the multicenter Heart And Lung Failure-Pediatric INsulin Titration trial. SETTING:Thirty-five PICUs. PATIENTS:Critically ill children with hyperglycemia who received the Heart And Lung Failure-Pediatric INsulin Titration protocol from 2012 to 2016. INTERVENTIONS:Randomization to a lower versus higher glucose target group. MEASUREMENTS AND MAIN RESULTS:Of 698 patients analyzed, 48 (7%) never developed multiple organ dysfunction syndrome, 549 (79%) had multiple organ dysfunction syndrome without progression, 32 (5%) developed new multiple organ dysfunction syndrome, and 69 (10%) developed progressive multiple organ dysfunction syndrome. Of those whose multiple organ dysfunction syndrome resolved, 192 (34%) experienced recurrent multiple organ dysfunction syndrome. There were no significant differences in the proportion of multiple organ dysfunction syndrome subgroups between Heart And Lung Failure-Pediatric INsulin Titration glucose target groups. However, patients with new or progressive multiple organ dys function syndrome had fewer ICU-free days through day 28 than those without new or progressive multiple organ dysfunction syndrome, and progressive multiple organ dysfunction syndrome patients had fewer ICU-free days than those with new multiple organ dysfunction syndrome: median 25.1 days for never multiple organ dysfunction syndrome, 20.2 days for multiple organ dysfunction syndrome without progression, 18.6 days for new multiple organ dysfunction syndrome, and 0 days for progressive multiple organ dysfunction syndrome (all comparisons p < 0.001). Patients with recurrent multiple organ dysfunction syndrome experienced fewer ICU-free days than those without recurrence (median, 11.2 vs 22.8 d; p < 0.001). CONCLUSIONS:Tight glycemic control target range was not associated with differences in the proportion of new, progressive, or recurrent multiple organ dysfunction syndrome. New or progressive multiple organ dysfunction syndrome was associated with poor clinical outcomes, and progressive multiple organ dysfunction syndrome was associated with worse outcomes than new multiple organ dysfunction syndrome. In future studies, new multiple organ dysfunction syndrome and progressive multiple organ dysfunction syndrome may need to be considered separately, as they represent distinct subgroups with different, potentially modifiable risk factors. Patients with recurrent multiple organ dysfunction syndrome represent a newly characterized, high-risk group which warrants attention in future research.

Project description:BackgroundDiabetic kidney disease (DKD) is a leading cause of end-stage renal disease; however, the underlying molecular mechanisms remain unclear. Recently, bioinformatics analysis has provided a comprehensive insight toward the molecular mechanisms of DKD. Here, we re-analyzed three mRNA microarray datasets including a single-cell RNA sequencing (scRNA-seq) dataset, with the aim of identifying crucial genes correlated with DKD and contribute to a better understanding of DKD pathogenesis.MethodsThree datasets including GSE131882, GSE30122, and GSE30529 were utilized to find differentially expressed genes (DEGs). The potential functions of DEGs were analyzed by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. A protein-protein interaction (PPI) network was constructed, and hub genes were selected with the top three molecular complex detection (MCODE) score. A correlation analysis between hub genes and clinical indicators was also performed.ResultsIn total, 84 upregulated DEGs and 49 downregulated DEGs were identified. Enriched pathways of the upregulated DEGs included extracellular matrix (ECM) receptor interaction, focal adhesion, human papillomavirus infection, malaria, and cell adhesion molecules. The downregulated DEGs were mainly enriched in ascorbate and aldarate metabolism, arginine and proline metabolism, endocrine- and other factor-regulated calcium reabsorption, mineral absorption and longevity regulating pathway, and multiple species signaling pathway. Seventeen hub genes were identified, and correlation analysis between unexplored hub genes and clinical features of DKD suggested that EGF, KNG1, GADD45B, and CDH2 might have reno-protective roles in DKD. Meanwhile, ATF3, B2M, VCAM1, CLDN4, SPP1, SOX9, JAG1, C3, and CD24 might promote the progression of DKD. Finally, most hub genes were found present in the immune cells of diabetic kidneys, which suggest the important role of inflammation infiltration in DKD pathogenesis.ConclusionsIn this study, we found seventeen hub genes using a scRNA-seq contained multiple-microarray analysis, which enriched the present understanding of molecular mechanisms underlying the pathogenesis of DKD in cells' level and provided candidate targets for diagnosis and treatment of DKD.

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Identification of genes and pathways associated with multiple organ dysfunction syndrome by microarray analysis.

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Identification of genes and pathways associated with multiple organ dysfunction syndrome by microarray analysis.

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