Evidence map›Paper›PMID 28826941›Full record

ReviewTrends in immunology2017

Mechanisms of Mixed Chimerism-Based Transplant Tolerance.

Julien Zuber, Megan Sykes

Open access · greenAbstract readReview
In one paragraph

Review in Trends in immunology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed
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.

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

47 citing papers in PubMed, 91 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Cytokines in transplantation tolerance.Best practice & research. Clinical haematology · 2025
    Review
  9. Unlocking Transplant Tolerance with Biomaterials.Advanced healthcare materials · 2025
    Review
  10. Tolerance Induction Strategies in Organ Transplantation: Current Status and Future Perspectives.Transplant international : official journal of the European Society for Organ Transplantation · 2025
    Review
  11. Review
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Helical TomoTherapy Total Lymphoid Irradiation and Hematopoietic Cell Transplantation for Kidney Transplant Tolerance in Rhesus Macaques.Transplant international : official journal of the European Society for Organ Transplantation · 2023
    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 at 2 institutions in 2 countries.

Julien ZuberService de Transplantation Rénale, Hôpital Necker, Université Paris Descartes, Paris, France; INSERM UMRS_1163, IHU Imagine, Paris, France. Electronic address: julien.zuber@aphp.fr.
Megan SykesColumbia Center for Translational Immunology, Department of Medicine, Columbia University, New York, NY 10032, USA; Department of Surgery, Columbia University, New York, NY 10032, USA; Department of Microbiology and Immunology, Columbia University Center, New York, NY 10032, USA. Electronic address: ms3976@cumc.columbia.edu.
Columbia University · USInserm · FR

Funding

Immune Tolerance Network UM1 2023 SupplementUM1AI109565 · NIAID · BENAROYA RESEARCH INST AT VIRGINIA MASON · PI Mark S Anderson, Jane Hoyt Buckner · 2014 to 2026
$451.6M
XENOGRAFT TOLERANCE THROUGH MIXED CHIMERISMP01AI045897 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI Megan Sykes · 2000 to 2026
$71.9M
XENOGENIC TOLERANCE IN MICEP01HL018646 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI MADSEN, JOREN C · 1985 to 2019
$37.5M
Transcriptomics and Repertoire ProfilingP01AI106697 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Donna L. Farber · 2013 to 2026
$31.3M
Robust allograft tolerance in non-human primatesR01OD017949 · OD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SYKES, MEGAN · 2015 to 2019
$4.5M
Mice with autologous human T1D-derived immune systems and iPSC-derived beta cellsUC4DK104207 · NIDDK · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SYKES, MEGAN · 2014 to 2014
$3.8M
Immune Response to iPSC-Derived Beta Cells in Type 1 DiabetesR01DK103585 · NIDDK · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SYKES, MEGAN · 2015 to 2018
$1.8M
Immune response to combined liver and bone marrow transplant for tolerance in NHPR56AI122332 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SYKES, MEGAN · 2016 to 2016
$320k
NHLBI NIH HHS P01 HL018646NIAID NIH HHS P01 AI045897NIAID NIH HHS P01 AI106697NIAID NIH HHS R56 AI122332NIAID NIH HHS UM1 AI109565NIDDK NIH HHS R01 DK103585NIDDK NIH HHS UC4 DK104207NIH HHS R01 OD017949
6 · The paper itself

Abstract

Immune responses to allografts represent a major barrier in organ transplantation. Immune tolerance to avoid chronic immunosuppression is a critical goal in the field, recently achieved in the clinic by combining bone marrow transplantation (BMT) with kidney transplantation following non-myeloablative conditioning. At high levels of chimerism such protocols can permit central deletional tolerance, but with a significant risk of graft-versus-host (GVH) disease (GVHD). By contrast, transient chimerism-based tolerance is devoid of GVHD risk and appears to initially depend on regulatory T cells (Tregs) followed by gradual, presumably peripheral, clonal deletion of donor-reactive T cells. Here we review recent mechanistic insights into tolerance and the development of more robust and safer protocols for tolerance induction that will be guided by innovative immune monitoring tools.

Indexed as

ChimerismTransplantation ImmunologyTransplantation ToleranceAnimalsBone Marrow TransplantationClonal DeletionHumansKidney TransplantationT-Lymphocytes, RegulatoryTransplantation ChimeraTransplantation Conditioningclonal deletionmixed chimerismregulatory T cellstolerance

Identifiers

PMID28826941
PMCPMC5669809
OpenAlexW2746174184

What OpenQuestion holds

Textmetadata
LicenceTDM
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.