Evidence map›Paper›PMID 27452608›Full record

Trial reportLancet (London, England)2016

Biopsy transcriptome expression profiling to identify kidney transplants at risk of chronic injury: a multicentre, prospective study.

Philip J O'Connell, Weijia Zhang, Madhav C Menon, Zhengzi Yi, Bernd Schröppel, Lorenzo Gallon, Yi Luan, Ivy A Rosales, Yongchao Ge, Bojan Losic and 16 more

2 registry-linked trialsAbstract readClinical TrialMulticenter Study
In one paragraph

Trial report in Lancet (London, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 84 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
84citing papers in PubMed, 1 pooled it
16.4field-weighted citation impact, top 1% of its field
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.

NCT00611702 completednot on this map

Genomics of Chronic Renal Allograft Rejection

TypeobservationalSponsorNational Institute of Allergy and Infectious Diseases (NIAID)Ran2008 to 2013Enrolled588ConditionsKidney TransplantationArmsKidney biopsy
NCT05378282 completednot on this mapstarted 2021, after this paper: background citation

Identification of Diabetic Nephropathy Biomarkers Through Transcriptomics

TypeobservationalSponsorHospital Juarez de MexicoRan2021 to 2023Enrolled40ConditionsType 2 Diabetes, Type 2 Diabetes With Renal Manifestations
3 · Its place in the literature

Who cites it

84 citing papers in PubMed, 1 synthesis or guideline pooled it, 179 citations in OpenAlex.

  1. Genome-wide donor-recipient non-HLA mismatch and graft loss.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2025
    Pooled it
  2. Trial
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Noninvasive Diagnosis of Kidney Allograft Rejection.Journal of the American Society of Nephrology : JASN · 2025
    Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Biomarkers of Rejection in Kidney Transplantation.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2025
    Review
  15. Article
  16. Article
  17. Trained immunity suppression determines kidney allograft survival.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2024
    Article
  18. Article
  19. Review
  20. Review

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

26 authors at 8 institutions in 2 countries.

Philip J O'ConnellRenal Unit, University of Sydney at Westmead Hospital, Sydney, NSW, Australia.
Weijia ZhangDivision of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Madhav C MenonDivision of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Zhengzi YiDivision of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Bernd SchröppelDivision of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Lorenzo GallonDepartment of Medicine-Nephrology and Surgery-Organ Transplantation, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Yi LuanDivision of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Ivy A RosalesDepartment of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Yongchao GeDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Bojan LosicDepartment of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Caixia XiDivision of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Christopher WoytovichDivision of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Karen L KeungDivision of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Chengguo WeiDivision of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Ilana GreeneDivision of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Jessica OverbeyDepartment of Health Evidence and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Emilia BagiellaDepartment of Health Evidence and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Nader NajafianDepartment of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Milagros SamaniegoDivision of Nephrology, Department of Medicine, University of Michigan, Ann Arbor, MI, USA.
Arjang DjamaliDivision of Nephrology, Department of Medicine, University of Wisconsin, Madison, WI, USA.
Stephen I AlexanderDiscipline of Child & Adolescent Health, The Children's Hospital at Westmead Clinical School, The University of Sydney, NSW, Australia.
Brian J NankivellRenal Unit, University of Sydney at Westmead Hospital, Sydney, NSW, Australia.
Jeremy R ChapmanRenal Unit, University of Sydney at Westmead Hospital, Sydney, NSW, Australia.
Rex Neal SmithDepartment of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Robert ColvinDepartment of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Barbara MurphyDivision of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Electronic address: barbara.murphy@mountsinai.org.
Icahn School of Medicine at Mount Sinai · USHarvard University · USThe University of Sydney · AUBrigham and Women's Hospital · USNorthwestern University · USUniversity of Michigan · USUniversity of Wisconsin–Madison · USWestmead Hospital · AU

Funding

ZIPRASIDONE (GEODON) AUGMENTATION IN SEROTONIN REUPTAKE INHIBITOR-RESISTANT OBM01RR000071 · NCRR · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI NEWCORN, JEFFREY H · 1985 to 2009
$41.5M
Genomics of Chronic Renal Allograft RejectionU01AI070107 · NIAID · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI MURPHY, BARBARA T. · 2006 to 2012
$9.4M
NCRR NIH HHS M01 RR000071NIAID NIH HHS U01 AI070107PHS HHS 5U01A1070107-03
6 · The paper itself

Abstract

backgroundChronic injury in kidney transplants remains a major cause of allograft loss. The aim of this study was to identify a gene set capable of predicting renal allografts at risk of progressive injury due to fibrosis.

methodsThis Genomics of Chronic Allograft Rejection (GoCAR) study is a prospective, multicentre study. We prospectively collected biopsies from renal allograft recipients (n=204) with stable renal function 3 months after transplantation. We used microarray analysis to investigate gene expression in 159 of these tissue samples. We aimed to identify genes that correlated with the Chronic Allograft Damage Index (CADI) score at 12 months, but not fibrosis at the time of the biopsy. We applied a penalised regression model in combination with permutation-based approach to derive an optimal gene set to predict allograft fibrosis. The GoCAR study is registered with ClinicalTrials.gov, number NCT00611702.

findingsWe identified a set of 13 genes that was independently predictive for the development of fibrosis at 1 year (ie, CADI-12 ≥2). The gene set had high predictive capacity (area under the curve [AUC] 0·967), which was superior to that of baseline clinical variables (AUC 0·706) and clinical and pathological variables (AUC 0·806). Furthermore routine pathological variables were unable to identify which histologically normal allografts would progress to fibrosis (AUC 0·754), whereas the predictive gene set accurately discriminated between transplants at high and low risk of progression (AUC 0·916). The 13 genes also accurately predicted early allograft loss (AUC 0·842 at 2 years and 0·844 at 3 years). We validated the predictive value of this gene set in an independent cohort from the GoCAR study (n=45, AUC 0·866) and two independent, publically available expression datasets (n=282, AUC 0·831 and n=24, AUC 0·972).

interpretationOur results suggest that this set of 13 genes could be used to identify kidney transplant recipients at risk of allograft loss before the development of irreversible damage, thus allowing therapy to be modified to prevent progression to fibrosis.

fundingNational Institutes of Health.

Indexed as

AdolescentAdultAgedAged, 80 and overBiopsyFibrosisGene Expression ProfilingGenetic TestingGraft RejectionHumansKidneyKidney TransplantationMaleMiddle AgedProspective StudiesRenal Insufficiency, Chronic

Identifiers

PMID27452608
PMCPMC5014570
OpenAlexW2486032828

What OpenQuestion holds

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LicenceTDM
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Registered trials

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.