Evidence map›Paper›PMID 28188669›Full record

ArticleAmerican journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons2017

Orthogonal Comparison of Molecular Signatures of Kidney Transplants With Subclinical and Clinical Acute Rejection: Equivalent Performance Is Agnostic to Both Technology and Platform.

S M Kurian, E Velazquez, R Thompson, T Whisenant, S Rose, N Riley, F Harrison, T Gelbart, J J Friedewald, J Charette and 5 more

Registry-linked trialOpen access · hybridAbstract read
In one paragraph

Article in American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05335538 (The Role of TruGraf® to Optimize Outcomes in Pediatric Renal Transplantation), which is not on this map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
4.8field-weighted citation impact, top 4% 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.

NCT05335538 unknown statusnot on this mapstarted 2021, after this paper: background citation

The Role of TruGraf® to Optimize Outcomes in Pediatric Renal Transplantation

TypeobservationalSponsorTransplant Genomics, Inc.Ran2021 to 2023Enrolled75ConditionsKidney Transplant RejectionArmsPatients monitored with TruGraf and TRAC testing
3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 38 citations in OpenAlex.

  1. Article
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  6. Review
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  11. Review
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  14. Discovery and cross-validation of peripheral blood and renal biopsy gene expression signatures from ethnically diverse kidney transplant populations.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2019
    Article
  15. Development and clinical validity of a novel blood-based molecular biomarker for subclinical acute rejection following kidney transplant.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2019
    Observational
  16. Single nucleotide variant counts computed from RNA sequencing and cellular traffic into human kidney allografts.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2018
    Article
  17. Review
  18. Article
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

15 authors at 3 institutions in 1 country.

S M KurianDepartment of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA.
E VelazquezDepartment of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA.
R ThompsonDepartment of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA.
T WhisenantDepartment of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA.
S RoseTransplant Genomics Inc., Mansfield, MA.
N RileyDepartment of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA.
F HarrisonDepartment of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA.
T GelbartDepartment of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA.
J J FriedewaldComprehensive Transplant Center, Feinberg School of Medicine, Northwestern University, Chicago, IL.ORCID http://orcid.org/0000-0002-9344-9928
J CharetteComprehensive Transplant Center, Feinberg School of Medicine, Northwestern University, Chicago, IL.
S BrietigamComprehensive Transplant Center, Feinberg School of Medicine, Northwestern University, Chicago, IL.
J PeysakhovichComprehensive Transplant Center, Feinberg School of Medicine, Northwestern University, Chicago, IL.
M R FirstTransplant Genomics Inc., Mansfield, MA.
M M AbecassisComprehensive Transplant Center, Feinberg School of Medicine, Northwestern University, Chicago, IL.ORCID http://orcid.org/0000-0001-9333-463X
D R SalomonDepartment of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA.
Scripps Research Institute · USNorthwestern University · USMansfield University · US

Funding

Quantitative Biology CoreU19AI063603 · NIAID · SCRIPPS RESEARCH INSTITUTE, THE · PI YATES III, JOHN R · 2004 to 2015
$26.4M
NIAID NIH HHS U19 AI063603
6 · The paper itself

Abstract

We performed orthogonal technology comparisons of concurrent peripheral blood and biopsy tissue samples from 69 kidney transplant recipients who underwent comprehensive algorithm-driven clinical phenotyping. The sample cohort included patients with normal protocol biopsies and stable transplant (sTx) function (n = 25), subclinical acute rejection (subAR, n = 23), and clinical acute rejection (cAR, n = 21). Comparisons between microarray and RNA sequencing (RNA-seq) signatures were performed and demonstrated a strong correlation between the blood and tissue compartments for both technology platforms. A number of shared differentially expressed genes and pathways between subAR and cAR in both platforms strongly suggest that these two clinical phenotypes form a continuum of alloimmune activation. SubAR is associated with fewer or less expressed genes than cAR in blood, whereas in biopsy tissues, this clinical phenotype demonstrates a more robust molecular signature for both platforms. The discovery work done in this study confirms a clear ability to detect gene expression profiles for sTx, subAR, and cAR in both blood and biopsy tissue, yielding equivalent predictive performance that is agnostic to both technology and platform. Our data also provide strong biological insights into the molecular mechanisms underlying these signatures, underscoring their logistical potential as molecular diagnostics to improve clinical outcomes following kidney transplantation.

Indexed as

Gene Expression ProfilingAdultAgedBiomarkersCase-Control StudiesFemaleFollow-Up StudiesGraft RejectionGraft SurvivalHigh-Throughput Nucleotide SequencingHumansKidney Failure, ChronicKidney TransplantationMaleMiddle AgedPrevalenceBiomarkersclinical research/practicediagnostic techniques and imaginggenomicskidney (allograft) function/dysfunctionkidney transplantation/nephrologymicroarray/gene arrayrejection: acutetranslational research/science

Identifiers

PMID28188669
PMCPMC5519433
OpenAlexW2587563910

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.