Evidence map›Paper›PMID 21658299›Full record

ArticleGenome medicine2011

Biomarkers in solid organ transplantation: establishing personalized transplantation medicine.

Silke Roedder, Matthew Vitalone, Purvesh Khatri, Minnie M Sarwal

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

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

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Review
  8. Osteopontin and Transplantation: Where Are We Now?Archivum immunologiae et therapiae experimentalis · 2021
    Review
  9. Single cell immune profiling in transplantation research.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2019
    Review
  10. Review
  11. Article
  12. The association of urinary interferon-gamma inducible protein-10 (IP10/CXCL10) levels with kidney allograft rejection.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2017
    Article
  13. Article
  14. Article
  15. Article
  16. Advances in diagnostics for transplant rejection.Expert review of molecular diagnostics · 2016
    Review
  17. Article
  18. Through a glass darkly: seeking clarity in preventing late kidney transplant failure.Journal of the American Society of Nephrology : JASN · 2015
    Review
  19. Review
  20. Genomics of liver transplant injury and regeneration.Transplantation reviews (Orlando, Fla.) · 2015
    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

4 authors.

Silke RoedderDepartment of Pediatrics and Immunology, Stanford University, G306 300 Pasteur Drive, Palo Alto, CA 94304, USA. msarwal@stanford.edu.
Matthew Vitalone
Purvesh Khatri
Minnie M Sarwal

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Technological advances in molecular and in silico research have enabled significant progress towards personalized transplantation medicine. It is now possible to conduct comprehensive biomarker development studies of transplant organ pathologies, correlating genomic, transcriptomic and proteomic information from donor and recipient with clinical and histological phenotypes. Translation of these advances to the clinical setting will allow assessment of an individual patient's risk of allograft damage or accommodation. Transplantation biomarkers are needed for active monitoring of immunosuppression, to reduce patient morbidity, and to improve long-term allograft function and life expectancy. Here, we highlight recent pre- and post-transplantation biomarkers of acute and chronic allograft damage or adaptation, focusing on peripheral blood-based methodologies for non-invasive application. We then critically discuss current findings with respect to their future application in routine clinical transplantation medicine. Complement-system-associated SNPs present potential biomarkers that may be used to indicate the baseline risk for allograft damage prior to transplantation. The detection of antibodies against novel, non-HLA, MICA antigens, and the expression of cytokine genes and proteins and cytotoxicity-related genes have been correlated with allograft damage and are potential post-transplantation biomarkers indicating allograft damage at the molecular level, although these do not have clinical relevance yet. Several multi-gene expression-based biomarker panels have been identified that accurately predicted graft accommodation in liver transplant recipients and may be developed into a predictive biomarker assay.

Identifiers

PMID21658299
PMCPMC3218811

What OpenQuestion holds

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Registered trials

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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.