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    Serum metabolite concentrations and decreased GFR in the general population.
        
        Am. J. Kidney Dis. 60, 197-206 (2012)
    
    
    
				Background: Metabolites such as creatinine and urea are established kidney function markers. High-throughput metabolomic studies have not been reported in large general population samples spanning normal kidney function and chronic kidney disease (CKD). Study Design: Cross-sectional observational studies of the general population. Setting & Participants: 2 independent samples: KORA F4 (discovery sample, n = 3,011) and TwinsUK (validation sample, n = 984). Exposure Factors: 151 serum metabolites, quantified by targeted mass spectrometry. Outcomes & Measurements: Metabolites and their 22,650 ratios were analyzed by multivariable-adjusted linear regression for their association with glomerular filtration rate (eGFR), estimated separately from creatinine and cystatin C levels by CKD-EPI (CKD Epidemiology Collaboration) equations. After correction for multiple testing, significant metabolites (P < 3.3 x 10(-4) for single metabolites; P < 2.2 x 10(-6) for ratios) were meta-analyzed with independent data from the TwinsUK Study. Results: Replicated associations with eGFR were observed for 22 metabolites and 516 metabolite ratios. Pooled P values ranged from 7.1 x 10(-7) to 1.8 x 10(-69) for the replicated single metabolites. Acylcarnitines such as glutarylcarnitine were associated inversely with eGFR (-3.73 mL/min/1.73 m(2) per standard deviation [SD] increase, pooled P = 1.8 x 10(-69)). The replicated ratio with the strongest association was the ratio of serine to glutarylcarnitine (P = 3.6 x 10(-81)). Almost all replicated phenotypes associated with decreased eGFR (<60 mL/min/1.73 m(2); n = 172 cases) in KORA F4: per 1-SD increment, ORs ranged from 0.29-2.06. Across categories of a metabolic score consisting of 3 uncorrelated metabolites, the prevalence of decreased eGFR increased from 3% to 53%. Limitations: Cross-sectional study design, GFR was estimated, limited number of metabolites. Conclusions: Distinct metabolic phenotypes were reproducibly associated with eGFR in 2 separate population studies. They may provide novel insights into renal metabolite handling, improve understanding of pathophysiology, or aid in the diagnosis of kidney disease. Longitudinal studies are needed to clarify whether changes in metabolic phenotypes precede or result from kidney function impairment.
			
			
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        Publikationstyp
        Artikel: Journalartikel
    
 
    
        Dokumenttyp
        Wissenschaftlicher Artikel
    
 
     
    
    
        Schlagwörter
        Metabolomics ; Metabolites ; Estimated Glomerular Filtration Rate ; Chronic Kidney Disease; Glomerular-Filtration-Rate; Chronic Kidney-Disease; Renal-Disease; Uric-Acid; Creatinine; Immunosuppression; Dimethylarginine; Acylcarnitines; Association; Calibration
    
 
     
    
    
        Sprache
        englisch
    
 
    
        Veröffentlichungsjahr
        2012
    
 
     
    
        HGF-Berichtsjahr
        2012
    
 
    
    
        ISSN (print) / ISBN
        0272-6386
    
 
    
        e-ISSN
        1523-6838
    
 
     
     
     
	     
	 
	 
    
        Zeitschrift
        American Journal of Kidney Diseases
    
 
		
    
        Quellenangaben
        
	    Band: 60,  
	    Heft: 2,  
	    Seiten: 197-206 
	    
	    
	
    
 
  
         
        
            Verlag
            Elsevier
        
 
         
	
         
         
         
         
         
	
         
         
         
    
         
         
         
         
         
         
         
    
        Begutachtungsstatus
        Peer reviewed
    
 
    
        Institut(e)
        Institute of Epidemiology (EPI)
Institute of Genetic Epidemiology (IGE)
Research Unit Molecular Epidemiology (AME)
Molekulare Endokrinologie und Metabolismus (MEM)
Institute of Bioinformatics and Systems Biology (IBIS)
Institute of Experimental Genetics (IEG)
 
    Institute of Genetic Epidemiology (IGE)
Research Unit Molecular Epidemiology (AME)
Molekulare Endokrinologie und Metabolismus (MEM)
Institute of Bioinformatics and Systems Biology (IBIS)
Institute of Experimental Genetics (IEG)
        POF Topic(s)
        30202 - Environmental Health
30501 - Systemic Analysis of Genetic and Environmental Factors that Impact Health
30201 - Metabolic Health
30505 - New Technologies for Biomedical Discoveries
90000 - German Center for Diabetes Research
 
    30501 - Systemic Analysis of Genetic and Environmental Factors that Impact Health
30201 - Metabolic Health
30505 - New Technologies for Biomedical Discoveries
90000 - German Center for Diabetes Research
        Forschungsfeld(er)
        Genetics and Epidemiology
Enabling and Novel Technologies
 
    Enabling and Novel Technologies
        PSP-Element(e)
        G-504000-002
G-503900-002
G-504100-001
G-504200-003
G-505600-001
G-503700-001
G-501900-061
G-504090-001
 
     
     	
    G-503900-002
G-504100-001
G-504200-003
G-505600-001
G-503700-001
G-501900-061
G-504090-001
        PubMed ID
        22464876
    
    
    
        WOS ID
        WOS:000306477200007
    
    
        Scopus ID
        84863988304
    
    
        Erfassungsdatum
        2012-09-21