Evidence map›Paper›PMID 20093355›Full record

ArticleJournal of the American Society of Nephrology : JASN2010

Molecular mechanisms of chronic kidney transplant rejection via large-scale proteogenomic analysis of tissue biopsies.

Aleksey Nakorchevsky, Johannes A Hewel, Sunil M Kurian, Tony S Mondala, Daniel Campbell, Steve R Head, Christopher L Marsh, John R Yates, Daniel R Salomon

Registry-linked trialOpen access · greenAbstract read
In one paragraph

Article in Journal of the American Society of Nephrology : JASN, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04670926 (Immunosuppression Management in Renal Transplant Recipients With Transplant Excellence Based on TruGraf Test), which is not on this map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 pooled it
6.3field-weighted citation impact, top 3% 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.

NCT04670926 naunknown statusnot on this mapstarted 2021, after this paper: background citation

Immunosuppression Management in Renal Transplant Recipients With Transplant Excellence Based on TruGraf Test

TypeinterventionalSponsorTransplant Genomics, Inc.Ran2021 to 2023Enrolled75ConditionsKidney Transplant Rejection, ImmunosuppressionArmsTruGraf, Standard of Care
3 · Its place in the literature

Who cites it

41 citing papers in PubMed, 1 synthesis or guideline pooled it, 79 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Review
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
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  15. Article
  16. Review
  17. The Optimal PEG for Kidney Preservation: A Preclinical Porcine Study.International journal of molecular sciences · 2018
    Article
  18. Biomarkers in renal transplantation: An updated review.World journal of transplantation · 2017
    Review
  19. Transplant genetics and genomics.Nature reviews. Genetics · 2017
    Review
  20. Advances in diagnostics for transplant rejection.Expert review of molecular diagnostics · 2016
    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

9 authors at 3 institutions in 2 countries.

Aleksey NakorchevskyDepartment of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA 92037, USA.
Johannes A Hewel
Sunil M Kurian
Tony S Mondala
Daniel Campbell
Steve R Head
Christopher L Marsh
John R Yates
Daniel R Salomon
Scripps Research Institute · USScripps Health · USUniversity of Toronto · CA

Funding

ZDS2P REGULATES SWE1P-DEPENDENT POLARIZED CELL GROWTH IN S CEREVISIAEP41RR011823 · NCRR · UNIVERSITY OF WASHINGTON · PI SALVESEN, GUY S. · 1996 to 2011
$24.7M
Expression and function of the human PERV A receptorsR01AI052349 · NIAID · SCRIPPS RESEARCH INSTITUTE · PI SALOMON, DANIEL R. · 2002 to 2005
$1.7M
Expression and function of the human PERV A receptorsR56AI052349 · NIAID · SCRIPPS RESEARCH INSTITUTE, THE · PI SALOMON, DANIEL R. · 2007 to 2007
$426k
NCRR NIH HHS P41 RR011823NIAID NIH HHS R01 AI052349NIAID NIH HHS R56 AI052349NIAID NIH HHS U19AI52349
6 · The paper itself

Abstract

The most common cause of kidney transplant failure is the poorly characterized histopathologic entity interstitial fibrosis and tubular atrophy (IFTA). There are no known unifying mechanisms, no effective therapy, and no proven preventive strategies. Possible mechanisms include chronic immune rejection, inflammation, drug toxicity, and chronic kidney injury from secondary factors. To gain further mechanistic insight, we conducted a large-scale proteogenomic study of kidney transplant biopsies with IFTA of varying severity. We acquired proteomic data using tandem mass spectrometry with subsequent quantification, analysis of differential protein expression, validation, and functional annotations to known molecular networks. We performed genome-wide expression profiling in parallel. More than 1400 proteins with unique expression profiles traced the progression from normal transplant biopsies to biopsies with mild to moderate and severe disease. Multiple sets of proteins were mapped to different functional pathways, many increasing with histologic severity, including immune responses, inflammatory cell activation, and apoptosis consistent with the chronic rejection hypothesis. Two examples include the extensive population of the alternative rather than the classical complement pathway, previously not appreciated for IFTA, and a comprehensive control network for the actin cytoskeleton and cell signaling of the acute-phase response. In summary, this proteomic effort using kidney tissue contributes mechanistic insight into several biologic processes associated with IFTA.

Indexed as

Kidney TransplantationProteomicsAdultAgedAtrophyBiopsyCytoskeletonFemaleFibrosisGraft RejectionHumansKidneyMaleMiddle AgedSignal Transduction

Identifiers

PMID20093355
PMCPMC2834542
OpenAlexW2108304538

What OpenQuestion holds

Textmetadata
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.