Combining metabolomic non-targeted GC×GC-ToF-MS analysis and chemometric ASCA-based study of variances to assess dietary influence on type 2 diabetes development in a mouse model.
    
    
        
    
    
        
        Anal. Bioanal. Chem. 407, 343-354 (2015)
    
    
    
		
		
			
				Insulin resistance (IR) lies at the origin of type 2 diabetes. It induces initial compensatory insulin secretion until insulin exhaustion and subsequent excessive levels of glucose (hyperglycemia). A high-calorie diet is a major risk factor contributing to the development of this metabolic disease. For this study, a time-course experiment was designed that consisted of two groups of mice. The aim of this design was to reproduce the dietary conditions that parallel the progress of IR over time. The first group was fed with a high-fatty-acid diet for several weeks and followed by 1 week of a low-fatty-acid intake, while the second group was fed with a low-fatty-acid diet during the entire experiment. The metabolomic fingerprint of C3HeB/FeJ mice liver tissue extracts was determined by means of two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-ToF-MS). This article addresses the application of ANOVA-simultaneous component analysis (ASCA) to the found metabolomic profile. By performing hyphenated high-throughput analytical techniques together with multivariate chemometric methodology on metabolomic analysis, it enables us to investigate the sources of variability in the data related to each experimental factor of the study design (defined as time, diet and individual). The contribution of the diet factor in the dissimilarities between the samples appeared to be predominant over the time factor contribution. Nevertheless, there is a significant contribution of the time-diet interaction factor. Thus, evaluating the influences of the factors separately, as it is done in classical statistical methods, may lead to inaccurate interpretation of the data, preventing achievement of consistent biological conclusions.
			
			
				
			
		 
		
			
				
					
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        Publikationstyp
        Artikel: Journalartikel
    
 
    
        Dokumenttyp
        Wissenschaftlicher Artikel
    
 
    
        Typ der Hochschulschrift
        
    
 
    
        Herausgeber
        
    
    
        Schlagwörter
        Metabolomics; Chemometrics; Gas chromatography mass spectrometry; ANOVA-simulataneous component analysis (ASCA); Type II diabetes; Mouse model
    
 
    
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        Sprache
        englisch
    
 
    
        Veröffentlichungsjahr
        2015
    
 
    
        Prepublished im Jahr 
        2014
    
 
    
        HGF-Berichtsjahr
        2014
    
 
    
    
        ISSN (print) / ISBN
        1618-2642
    
 
    
        e-ISSN
        1618-2650
    
 
    
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	    Band: 407,  
	    Heft: 1,  
	    Seiten: 343-354 
	    Artikelnummer: ,  
	    Supplement: ,  
	
    
 
  
        
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            Verlag
            Springer
        
 
        
            Verlagsort
            Heidelberg
        
 
	
        
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        Begutachtungsstatus
        Peer reviewed
    
 
     
    
        POF Topic(s)
        30202 - Environmental Health
30501 - Systemic Analysis of Genetic and Environmental Factors that Impact Health
90000 - German Center for Diabetes Research
    
 
    
        Forschungsfeld(er)
        Environmental Sciences
Genetics and Epidemiology
    
 
    
        PSP-Element(e)
        G-504500-001
G-500600-002
G-501900-062
G-504091-003
    
 
    
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        Erfassungsdatum
        2014-12-01