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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.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Times Cited
Scopus
Cited By
Cited By
Altmetric
5.434
1.997
70
84
Anmerkungen
Besondere Publikation
Auf Hompepage verbergern
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