Evidence map›Paper›PMID 28286337›Full record

ReviewNature reviews. Genetics2017

Transplant genetics and genomics.

Joshua Y C Yang, Minnie M Sarwal

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
–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

39 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. An interleukin 6-based genetic risk score strengthened with interleukin 10 polymorphisms associated with long-term kidney allograft outcomes.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2022
    Article
  9. Review
  10. Article
  11. Review
  12. A functionalClinical kidney journal · 2022
    Article
  13. A practical approach to the genomics of kidney disorders.Pediatric nephrology (Berlin, Germany) · 2022
    Review
  14. Article
  15. Modeling the Potential of Treg-Based Therapies for Transplant Rejection: Effect of Dose, Timing, and Accumulation Site.Transplant international : official journal of the European Society for Organ Transplantation · 2022
    Article
  16. Review
  17. Article
  18. Article
  19. Review
  20. 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

2 authors.

Joshua Y C YangDivision of Transplant Surgery, University of California San Francisco, 513 Parnassus Avenue, San Francisco, California 94143, USA.
Minnie M SarwalDivision of Transplant Surgery, University of California San Francisco, 513 Parnassus Avenue, San Francisco, California 94143, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ever since the discovery of the major histocompatibility complex, scientific and clinical understanding in the field of transplantation has been advanced through genetic and genomic studies. Candidate-gene approaches and recent genome-wide association studies (GWAS) have enabled a deeper understanding of the complex interplay of the donor-recipient interactions that lead to transplant tolerance or rejection. Genetic analysis in transplantation, when linked to demographic and clinical outcomes, has the potential to drive personalized medicine by enabling individualized risk stratification and immunosuppression through the identification of variants associated with immune-mediated complications, post-transplant disease or alterations in drug-metabolizing genes.

Indexed as

Organ TransplantationPrecision MedicineGenetic Predisposition to DiseaseGenetic TestingGenetic VariationGenome-Wide Association StudyGenomicsGraft RejectionHumans

Identifiers

PMID28286337

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.