Evidence map›Paper›PMID 25011442›Full record

ArticleClinical journal of the American Society of Nephrology : CJASN2014

Serum metabolomic profiling and incident CKD among African Americans.

Bing Yu, Yan Zheng, Jennifer A Nettleton, Danny Alexander, Josef Coresh, Eric Boerwinkle

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Clinical journal of the American Society of Nephrology : CJASN, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

64 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Vegetarian Dietary Patterns and Diet-Related Metabolites Are Associated With Kidney Function in the Adventist Health Study-2 Cohort.Journal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation · 2026
    Article
  5. Article
  6. Article
  7. Review
  8. NADCell communication and signaling : CCS · 2024
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Review
  17. Biomarkers of aging.Science China. Life sciences · 2023
    Review
  18. Article
  19. Review
  20. Review

4 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Bing YuDivision of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas;
Yan ZhengDivision of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas;
Jennifer A NettletonDivision of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas;
Danny AlexanderMetabolon, Inc., Durham, North Carolina;
Josef CoreshDepartments of Epidemiology and Biostatistics, Johns Hopkins University, Baltimore, Maryland; and.
Eric BoerwinkleDivision of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas; Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas Eric.Boerwinkle@uth.tmc.edu.

Funding

GWA for Gene-Environment Interaction Effects Influencing CHDU01HG004402 · NHGRI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI BOERWINKLE, ERIC A. · 2007 to 2009
$1.6M
Interaction between diet and genetic variation: influence on Type 2 Diabetes riskK01DK082729 · NIDDK · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI NETTLETON, JENNIFER ANN · 2008 to 2011
$439k
NHGRI NIH HHS 3U01HG004402-02S1NHGRI NIH HHS U01 HG004402NHLBI NIH HHS HHSN268201100005CNHLBI NIH HHS HHSN268201100005GNHLBI NIH HHS HHSN268201100005INHLBI NIH HHS HHSN268201100006CNHLBI NIH HHS HHSN268201100007CNHLBI NIH HHS HHSN268201100007INHLBI NIH HHS HHSN268201100008CNHLBI NIH HHS HHSN268201100008INHLBI NIH HHS HHSN268201100009CNHLBI NIH HHS HHSN268201100009INHLBI NIH HHS HHSN268201100010CNHLBI NIH HHS HHSN268201100011CNHLBI NIH HHS HHSN268201100011INHLBI NIH HHS HHSN268201100012CNIDDK NIH HHS 5K01DK082729-04NIDDK NIH HHS K01 DK082729
6 · The paper itself

Abstract

BACKGROUND AND

objectivesNovel biomarkers that more accurately reflect kidney function and predict future CKD are needed. The human metabolome is the product of multiple physiologic or pathophysiologic processes and may provide novel insight into disease etiology and progression. This study investigated whether estimated kidney function would be associated with multiple metabolites and whether selected metabolomic factors would be independent risk factors for incident CKD. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: In total, 1921 African Americans free of CKD with a median of 19.6 years follow-up among the Atherosclerosis Risk in Communities Study were included. A total of 204 serum metabolites quantified by untargeted gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry was analyzed by both linear regression for the cross-sectional associations with eGFR (specified by the Chronic Kidney Disease Epidemiology Collaboration equation) and Cox proportional hazards model for the longitudinal associations with incident CKD.

resultsForty named and 34 unnamed metabolites were found to be associated with eGFR specified by the Chronic Kidney Disease Epidemiology Collaboration equation with creatine and 3-indoxyl sulfate showing the strongest positive (2.8 ml/min per 1.73 m(2) per +1 SD; 95% confidence interval, 2.1 to 3.5) and negative association (-14.2 ml/min per 1.73 m(2) per +1 SD; 95% confidence interval, -17.0 to -11.3), respectively. Two hundred four incident CKD events with a median follow-up time of 19.6 years were included in the survival analyses. Higher levels of 5-oxoproline (hazard ratio, 0.70; 95% confidence interval, 0.60 to 0.82) and 1,5-anhydroglucitol (hazard ratio, 0.68; 95% confidence interval, 0.58 to 0.80) were significantly related to lower risk of incident CKD, and the associations did not appreciably change when mutually adjusted.

conclusionsThese data identify a large number of metabolites associated with kidney function as well as two metabolites that are candidate risk factors for CKD and may provide new insights into CKD biomarker identification.

Indexed as

Black or African AmericanMetabolomicsBiomarkersChromatography, LiquidCreatineCross-Sectional StudiesDeoxyglucoseFemaleGas Chromatography-Mass SpectrometryHumansIncidenceIndicanKidneyLinear ModelsLongitudinal StudiesMale1,5-anhydroglucitolBiomarkersCreatineDeoxyglucoseIndicanPyrrolidonecarboxylic AcidAfrican-American Study of Kidney Disease and HypertensioncardiovascularCKDepidemiology and outcomesGFR

Identifiers

PMID25011442
PMCPMC4123405

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.