Evidence map›Paper›PMID 24517436›Full record

ReviewImmunological reviews2014

Urinary cell mRNA profiles predictive of human kidney allograft status.

John R Lee, Thangamani Muthukumar, Darshana Dadhania, Ruchuang Ding, Vijay K Sharma, Joseph E Schwartz, Manikkam Suthanthiran

Abstract readReview
In one paragraph

Review in Immunological reviews, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Recent Advances on Biomarkers of Early and Late Kidney Graft Dysfunction.International journal of molecular sciences · 2020
    Review
  13. An overview of frailty in kidney transplantation: measurement, management and future considerations.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2020
    Review
  14. Article
  15. Article
  16. Article
  17. Biomarkers in renal transplantation: An updated review.World journal of transplantation · 2017
    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

7 authors.

John R LeeDivision of Nephrology and Hypertension, Department of Medicine, Weill Cornell Medical College, New York, NY, USA; Department of Transplantation Medicine, New York Presbyterian Hospital - Weill Cornell Medical Center, New York, NY, USA.
Thangamani Muthukumar
Darshana Dadhania
Ruchuang Ding
Vijay K Sharma
Joseph E Schwartz
Manikkam Suthanthiran

Funding

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
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 RR 024996NIAID NIH HHS R37 AI051652NIAID NIH HHS R37-AI051652NIAID NIH HHS U01 AI063589NIDDK NIH HHS K08 DK087824NIDDK NIH HHS K08-DK087824PHS HHS UO1A163589
6 · The paper itself

Abstract

Kidney allograft status is currently characterized using the invasive percutaneous needle core biopsy procedure. The procedure has become safer over the years, but challenges and complications still exist including sampling error, interobserver variability, bleeding, arteriovenous fistula, graft loss, and even death. Because the most common type of acute rejection is distinguished by inflammatory cells exiting the intravascular compartment and gaining access to the renal tubular space, we reasoned that a kidney allograft may function as an in vivo flow cytometer and sort cells involved in rejection into urine. To test this idea, we developed quantitative polymerase chain reaction (PCR) assays for absolute quantification of mRNA and pre-amplification protocols to overcome the low RNA yield from urine. Here, we review our single center urinary cell mRNA profiling studies that led to the multicenter Clinical Trials in Organ Transplantation (CTOT-04) study and the discovery and validation of a 3-gene signature of 18S rRNA-normalized measures of CD3ε mRNA and IP-10 mRNA and 18S rRNA that is diagnostic and predictive of acute cellular rejection in the kidney allograft. We also review our development of a 4-gene signature of mRNAs for vimentin, NKCC2, E-cadherin, and 18S rRNA diagnostic of interstitial fibrosis/tubular atrophy (IF/TA).

Indexed as

Gene Expression ProfilingGenetic TestingKidney TransplantationAllograftsBiopsyGenetic MarkersGraft RejectionHumansPolymerase Chain ReactionPredictive Value of TestsRNA, MessengerTreatment OutcomeGenetic MarkersRNA, Messengeracute cellular rejectioninterstitial fibrosiskidney transplantationPCRurinary cell mRNA profiling

Identifiers

PMID24517436
PMCPMC3947569

What OpenQuestion holds

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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.