Evidence map›Paper›PMID 19251643›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2009

Identifying compartment-specific non-HLA targets after renal transplantation by integrating transcriptome and "antibodyome" measures.

Li Li, Persis Wadia, Rong Chen, Neeraja Kambham, Maarten Naesens, Tara K Sigdel, David B Miklos, Minnie M Sarwal, Atul J Butte

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed
6.9field-weighted citation impact, top 2% 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.

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

56 citing papers in PubMed, 102 citations in OpenAlex.

  1. Trial
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  8. Discovery of non-HLA antibodies associated with cardiac allograft rejection and development and validation of a non-HLA antigen multiplex panel: From bench to bedside.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2020
    Article
  9. Review
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  12. Biomarkers in Solid Organ Transplantation.Clinics in laboratory medicine · 2019
    Review
  13. Article
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  15. Article
  16. Review
  17. Transplant genetics and genomics.Nature reviews. Genetics · 2017
    Review
  18. The Emerging Importance of Non-HLA Autoantibodies in Kidney Transplant Complications.Journal of the American Society of Nephrology : JASN · 2017
    Review
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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 1 institution in 1 country.

Li LiDepartment of Pediatrics, Blood and Marrow Transplantation Division, Stanford University, 300 Pasteur Drive, Stanford, CA 94304, USA.
Persis Wadia
Rong Chen
Neeraja Kambham
Maarten Naesens
Tara K Sigdel
David B Miklos
Minnie M Sarwal
Atul J Butte
Stanford University · US

Funding

MOLECULAR &CELLULAR IMMUNOBIOLOGYT32AI007290 · NIAID · STANFORD UNIVERSITY · PI Sean Curtis Bendall, Olivia M Martinez · 1985 to 2026
$27.0M
Defining Biomarkers in Pediatric Renal TransplantationR01AI061739 · NIAID · STANFORD UNIVERSITY · PI SARWAL, MINNIE M · 2004 to 2007
$1.6M
CREATION AND APPLICATION OF A DIABETES KNOWLEDGE BASEK22LM008261 · NLM · STANFORD UNIVERSITY · PI BUTTE, ATUL J. · 2005 to 2007
$460k
NIAID NIH HHS R01 AI061739NIAID NIH HHS R01 AI61739NIAID NIH HHS T32 AI007290NLM NIH HHS K22 LM008261
6 · The paper itself

Abstract

We have conducted an integrative genomics analysis of serological responses to non-HLA targets after renal transplantation, with the aim of identifying the tissue specificity and types of immunogenic non-HLA antigenic targets after transplantation. Posttransplant antibody responses were measured by paired comparative analysis of pretransplant and posttransplant serum samples from 18 pediatric renal transplant recipients, measured against 5,056 unique protein targets on the ProtoArray platform. The specificity of antibody responses were measured against gene expression levels specific to the kidney, and 2 other randomly selected organs (heart and pancreas), by integrated genomics, employing the mapping of transcription and ProtoArray platform measures, using AILUN. The likelihood of posttransplant non-HLA targets being recognized preferentially in any of 7 microdissected kidney compartments was also examined. In addition to HLA targets, non-HLA immune responses, including anti-MICA antibodies, were detected against kidney compartment-specific antigens, with highest posttransplant recognition for renal pelvis and cortex specific antigens. The compartment specificity of selected antibodies was confirmed by IHC. In conclusion, this study provides an immunogenic and anatomic roadmap of the most likely non-HLA antigens that can generate serological responses after renal transplantation. Correlation of the most significant non-HLA antibody responses with transplant health and dysfunction are currently underway.

Indexed as

Antibody FormationGene Expression ProfilingAntibodiesAntibody SpecificityGenomicsHeartHumansKidneyKidney TransplantationOrgan SpecificityPancreasAntibodies

Identifiers

PMID19251643
PMCPMC2657434
OpenAlexW2130264854

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.