Platzer, A.* ; Nussbaumer, T. ; Karonitsch, T.* ; Smolen, J.S.* ; Aletaha, D.*
     
 
    
        
Analysis of gene expression in rheumatoid arthritis and related conditions offers insights into sex-bias, gene biotypes and co-expression patterns.
    
    
        
    
    
        
        PLoS ONE 14:e0219698 (2019)
    
    
    
		
		
			
				The era of next-generation sequencing has mounted the foundation of many gene expression studies. In rheumatoid arthritis research, this has led to the discovery of important candidate genes which offered novel insights into mechanisms and their possible roles in the cure of the disease. In the last years, data generation has outstripped data analysis and while many studies focused on specific aspects of the disease, a global picture of the disease is not yet accomplished. Here, we analyzed and compared a collection of gene expression information from healthy individuals and from patients suffering under different arthritis conditions from published studies containing the following clinical conditions: early and established rheumatoid arthritis, osteoarthritis and arthralgia. We show comprehensive overviews of this data collection and give new insights specifically on gene expression in the early stage, into sex-dependent gene expression, and we describe general differences in expression of different biotypes of genes. Many genes that are related to cytoskeleton changes (actin filament related genes) are differently expressed in early rheumatoid arthritis in comparison to healthy subjects; interestingly, eight of these genes reverse their expression ratio significantly between men and women compared early rheumatoid arthritis and healthy subjects. There are some slighter changes between men and woman between the conditions early and established rheumatoid arthritis. Another aspect are miRNAs and other gene biotypes which are not only promising candidates for diagnoses but also change their expression grossly in average at rheumatoid arthritis and arthralgia compared to the healthy condition. With a selection of intersecting genes, we were able to generate simple classification models to distinguish between healthy and rheumatoid arthritis as well as between early rheumatoid arthritis to other arthritides based on gene expression.
			
			
				
			
		 
		
			
				
					
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        Publikationstyp
        Artikel: Journalartikel
    
 
    
        Dokumenttyp
        Wissenschaftlicher Artikel
    
 
    
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        Sprache
        englisch
    
 
    
        Veröffentlichungsjahr
        2019
    
 
    
        Prepublished im Jahr 
        
    
 
    
        HGF-Berichtsjahr
        2019
    
 
    
    
        ISSN (print) / ISBN
        1932-6203
    
 
    
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	    Band: 14,  
	    Heft: 7,  
	    Seiten: ,  
	    Artikelnummer: e0219698 
	    Supplement: ,  
	
    
 
  
        
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            Verlag
            Public Library of Science (PLoS)
        
 
        
            Verlagsort
            Lawrence, Kan.
        
 
	
        
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        Begutachtungsstatus
        Peer reviewed
    
 
    
        Institut(e)
        Institute of Environmental Medicine (IEM)
Institute of Network Biology (INET)
    
 
    
        POF Topic(s)
        30202 - Environmental Health
30203 - Molecular Targets and Therapies
    
 
    
        Forschungsfeld(er)
        Allergy	
Environmental Sciences
    
 
    
        PSP-Element(e)
        G-503400-001
G-506400-001
    
 
    
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        Erfassungsdatum
        2019-08-06