4.6 Article

Serum Metabolite Concentrations and Decreased GFR in the General Population

期刊

AMERICAN JOURNAL OF KIDNEY DISEASES
卷 60, 期 2, 页码 197-206

出版社

W B SAUNDERS CO-ELSEVIER INC
DOI: 10.1053/j.ajkd.2012.01.014

关键词

Metabolomics; metabolites; estimated glomerular filtration rate; chronic kidney disease

资金

  1. German Federal Ministry of Education and Research (BMBF)
  2. German Research Foundation [KO 3598/2-1]
  3. BMBF [031 5896 A]
  4. Helmholtz Zentrum Munchen-National Research Center for Environmental Health
  5. German Federal Ministry of Education, Science, Research and Technology
  6. State of Bavaria
  7. Wellcome Trust
  8. European Community [HEALTH-F2-2008-201865-GEFOS, HEALTH-F4-2007-201413, QLG2-CT-2002-01254]
  9. UK Biotechnology and Biological Sciences Research Council [G20234]
  10. King's Business Innovation Development Fund
  11. Department of Health through the UK National Institute for Health Research

向作者/读者索取更多资源

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. Am J Kidney Dis. 60(2): 197-206. (C) 2012 by the National Kidney Foundation, Inc.

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