Evidence map›Paper›PMID 26047788›Full record

ArticleJournal of the American Society of Nephrology : JASN2016

Urine Metabolite Profiles Predictive of Human Kidney Allograft Status.

Karsten Suhre, Joseph E Schwartz, Vijay K Sharma, Qiuying Chen, John R Lee, Thangamani Muthukumar, Darshana M Dadhania, Ruchuang Ding, David N Ikle, Nancy D Bridges and 12 more

Abstract read
In one paragraph

Article in Journal of the American Society of Nephrology : JASN, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing 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

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

  1. Pooled it
  2. Review
  3. Article
  4. Observational
  5. NADTrends in molecular medicine · 2025
    Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Emerging monitoring technologies in kidney transplantation.Pediatric nephrology (Berlin, Germany) · 2021
    Review
  18. Article
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Karsten SuhreDepartment of Physiology and Biophysics, Weill Cornell Medical College in Qatar, Doha, Qatar; Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany;
Joseph E SchwartzDepartment of Psychiatry, Stony Brook University, Stony Brook, New York; Division of Nephrology and Hypertension, Departments of Medicine and Transplantation Medicine, New York Presbyterian Hospital-Weill Cornell Medical Center, New York, New York;
Vijay K SharmaDivision of Nephrology and Hypertension, Departments of Medicine and Transplantation Medicine, New York Presbyterian Hospital-Weill Cornell Medical Center, New York, New York;
Qiuying ChenDepartment of Pharmacology, Weill Cornell College of Medicine, New York, New York;
John R LeeDivision of Nephrology and Hypertension, Departments of Medicine and Transplantation Medicine, New York Presbyterian Hospital-Weill Cornell Medical Center, New York, New York;
Thangamani MuthukumarDivision of Nephrology and Hypertension, Departments of Medicine and Transplantation Medicine, New York Presbyterian Hospital-Weill Cornell Medical Center, New York, New York;
Darshana M DadhaniaDivision of Nephrology and Hypertension, Departments of Medicine and Transplantation Medicine, New York Presbyterian Hospital-Weill Cornell Medical Center, New York, New York;
Ruchuang DingDivision of Nephrology and Hypertension, Departments of Medicine and Transplantation Medicine, New York Presbyterian Hospital-Weill Cornell Medical Center, New York, New York;
David N IkleRho Federal Systems, Chapel Hill, North Carolina;
Nancy D BridgesNational Institute of Allergy and Infectious Diseases, Bethesda, Maryland;
Nikki M WilliamsNational Institute of Allergy and Infectious Diseases, Bethesda, Maryland;
Gabi KastenmüllerInstitute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany;
Edward D KarolyMetabolon, Inc., Durham, North Carolina;
Robert P MohneyMetabolon, Inc., Durham, North Carolina;
Michael AbecassisDivision of Surgery-Organ Transplantation, Northwestern University Feinberg School of Medicine, Chicago, Illinois;
John FriedewaldDivision of Nephrology-Organ Transplantation, Northwestern University Feinberg School of Medicine, Chicago, Illinois;
Stuart J KnechtleDivision of Surgery, Department of Surgery, University of Wisconsin Hospitals and Clinics, Madison, Wisconsin;
Yolanda T BeckerDivision of Surgery, Department of Surgery, University of Wisconsin Hospitals and Clinics, Madison, Wisconsin;
Benjamin SamsteinDivision of Transplantation, Department of Surgery, Columbia University College of Physicians and Surgeons, New York, New York; and.
Abraham ShakedDepartment of Surgery, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania.
Steven S GrossDepartment of Pharmacology, Weill Cornell College of Medicine, New York, New York;
Manikkam SuthanthiranDivision of Nephrology and Hypertension, Departments of Medicine and Transplantation Medicine, New York Presbyterian Hospital-Weill Cornell Medical Center, New York, New York; msuthan@med.cornell.edu.

Funding

Transplantation GroupUM2AI117870 · NIAID · RHO FEDERAL SYSTEMS DIVISION, INC. · PI DAVID, GLORIA · 2015 to 2023
$208.1M
CTSA INFRASTRUCTURE FOR PEDIATRIC RESEARCHUL1RR024996 · NCRR · WEILL MEDICAL COLL OF CORNELL UNIV · PI IMPERATO-MCGINLEY, JULIANNE L · 2007 to 2011
$49.6M
Clinical and Translational Science CenterUL1TR000457 · NCATS · WEILL MEDICAL COLL OF CORNELL UNIV · PI IMPERATO-MCGINLEY, JULIANNE L · 2012 to 2016
$46.0M
Molecular profiling and immunomodulatory interventionsU01AI063589 · NIAID · UNIVERSITY OF PENNSYLVANIA · PI SHAKED, ABRAHAM NA · 2004 to 2009
$14.4M
Biomolecular Markers for Safe Minimization of ImmunosuppressionR37AI051652 · NIAID · WEILL MEDICAL COLL OF CORNELL UNIV · PI SUTHANTHIRAN, MANIKKAM · 2009 to 2021
$4.7M
Diabetic Vasculopathy and Mitochondrial eNOSR37HL087062 · NHLBI · WEILL MEDICAL COLL OF CORNELL UNIV · PI GROSS, STEVEN S · 2007 to 2016
$4.2M
Clinical and Translational Science CenterKL2TR000458 · NCATS · WEILL MEDICAL COLL OF CORNELL UNIV · PI IMPERATO-MCGINLEY, JULIANNE L · 2012 to 2016
$2.1M
Biomolecular Markers of Renal Allograft StatusK08DK087824 · NIDDK · WEILL MEDICAL COLL OF CORNELL UNIV · PI MUTHUKUMAR, THANGAMANI · 2011 to 2015
$658k
NCATS NIH HHS KL2 TR000458NCATS NIH HHS KL2-TR000458NCATS NIH HHS UL1 TR000457NCRR NIH HHS UL1 RR024996NCRR NIH HHS ULI-RR024996NHLBI NIH HHS R37 HL087062NHLBI NIH HHS R37-HL087062NIAID NIH HHS R37 AI051652NIAID NIH HHS R37-AI051652NIAID NIH HHS U01 AI063589NIAID NIH HHS U01-AI63589NIAID NIH HHS UM2 AI117870NIDDK NIH HHS K08 DK087824NIDDK NIH HHS K08-DK087824
6 · The paper itself

Abstract

Noninvasive diagnosis and prognostication of acute cellular rejection in the kidney allograft may help realize the full benefits of kidney transplantation. To investigate whether urine metabolites predict kidney allograft status, we determined levels of 749 metabolites in 1516 urine samples from 241 kidney graft recipients enrolled in the prospective multicenter Clinical Trials in Organ Transplantation-04 study. A metabolite signature of the ratio of 3-sialyllactose to xanthosine in biopsy specimen-matched urine supernatants best discriminated acute cellular rejection biopsy specimens from specimens without rejection. For clinical application, we developed a high-throughput mass spectrometry-based assay that enabled absolute and rapid quantification of the 3-sialyllactose-to-xanthosine ratio in urine samples. A composite signature of ratios of 3-sialyllactose to xanthosine and quinolinate to X-16397 and our previously reported urinary cell mRNA signature of 18S ribosomal RNA, CD3ε mRNA, and interferon-inducible protein-10 mRNA outperformed the metabolite signatures and the mRNA signature. The area under the receiver operating characteristics curve for the composite metabolite-mRNA signature was 0.93, and the signature was diagnostic of acute cellular rejection with a specificity of 84% and a sensitivity of 90%. The composite signature, developed using solely biopsy specimen-matched urine samples, predicted future acute cellular rejection when applied to pristine samples taken days to weeks before biopsy. We conclude that metabolite profiling of urine offers a noninvasive means of diagnosing and prognosticating acute cellular rejection in the human kidney allograft, and that the combined metabolite and mRNA signature is diagnostic and prognostic of acute cellular rejection with very high accuracy.

Indexed as

Kidney TransplantationAcute DiseaseAdolescentAdultAgedAllograftsChildChild, PreschoolFemaleGraft RejectionHumansInfantKidneyMaleMiddle AgedPredictive Value of Testsacute rejectionkidney biopsyrenal transplantationtransplant outcomes

Identifiers

PMID26047788
PMCPMC4731125

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.