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Graft Rejection

Immunology · NLM MeSH · updated 2026-10-29 · version 1

Citations verified against PubMedNot yet clinician-reviewed9 referencesApproximately 4 min read

An immune response with both cellular and humoral components, directed against an allogeneic transplant, whose tissue antigens are not compatible with those of the recipient.

Table of Contents

1. Definition2. Research landscape3. Reading the evidence4. Open-access studies5. Key reviews6. References7. About this article

Definition and research guide

This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.

Content available: 3 complete abstracts (666 words), 9 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.

Definition

An immune response with both cellular and humoral components, directed against an allogeneic transplant, whose tissue antigens are not compatible with those of the recipient.

Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.

Also known as: Graft Rejections; Rejection, Graft; Rejections, Graft; Rejection, Transplant; Rejections, Transplant; Transplant Rejections; Transplant Rejection; Transplantation Rejection.

Where it fits in the MeSH classification

Broader topics
Host vs Graft Reaction
See also
Delayed Graft Function

Research landscape

PubMed indexes 68,521 records tagged with the MeSH heading “Graft Rejection” (counts retrieved 2026-10-29). 8,455 of them (12.3%) were published from 2020 onward, and the busiest period so far is through 1999 with 27,348 records.

Reviews account for 10,437 records (15.2%) and meta-analyses for 464. Randomized controlled trials number 1,981 (2.9%) as a share of all records on the topic.

PubMed records by publication periodthrough 1999: 27,348 records; 2000-2009: 15,868 records; 2010-2019: 16,850 records; 2020 onward: 8,455 records27,348through 199915,8682000-200916,8502010-20198,4552020 onward
Records in PubMed indexed with this heading, by publication period. Real counts from NCBI E-utilities; the final period covers only part of the current year. Volume reflects how much has been published, not how strong the evidence is.
Show the data
PeriodRecords
through 199927,348
2000-200915,868
2010-201916,850
2020 onward8,455
Share of records by publication typeReviews: 15.2 percent; Meta-analyses: 0.7 percent; Randomized controlled trials: 2.9 percentReviews15.2% (10,437)Meta-analyses0.7% (464)Randomized controlled trials2.9% (1,981)
Share of all PubMed records on this heading that carry each publication type. Types overlap with other records, so the shares do not sum to 100%.
Publication-type chart data
Publication types among 68,521 PubMed records
TypeRecordsShare
Reviews10,43715.2%
Meta-analyses4640.7%
Randomized controlled trials1,9812.9%

Method: PubMed query "Graft Rejection"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-29.

Reading the evidence in immunology

Immune responses are studied in model organisms, in cells from donors and in patients, and the same pathway can behave differently across these settings. Mouse immune systems differ from human ones in important ways, and blood measurements may not reflect what happens in tissues. Clinical conclusions about immune-mediated disease or immunotherapy come mainly from controlled trials and long-term cohorts. Check the species and tissue studied, whether markers were linked to outcomes patients notice, and the follow-up time.

Evidence from open-access studies

These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.

Study comparison — selected abstracts, not a systematic review
Study / authorsYearSource label / designEurope PMC citationsLicence / source
Injured epithelial cell states impact kidney allograft survival after T-cell-mediated rejection
Pfefferkorn AM, Jahn L, Gauthier PT, Kulow VA, Roeles J, Müller-Bötticher N, et al.
2026Research article
Design not recorded in structured metadata
5cc by
PMID 41605921 · DOI · PMC12852170
Development and validation of a bronchoalveolar lavage genomic classifier for acute cellular rejection
Weigt SS, Zhou J, Okuno T, Neely ML, Lari S, Palchevskiy V, et al.
2025Research article
Design not recorded in structured metadata
5cc by
PMID 41337937 · DOI · PMC12719680
Non-HLA antibody trajectories may predict kidney transplant outcomes
Rajalingam R, Sigdel TK, Maruthamuthu S, Raghav PK, Laszik ZG, Da Gente G, et al.
2026Research article
Design not recorded in structured metadata
4cc by
PMID 41816322 · DOI · PMC12971436

Injured epithelial cell states impact kidney allograft survival after T-cell-mediated rejection [1]

Research article Pfefferkorn AM, Jahn L, Gauthier PT, Kulow VA, Roeles J, Müller-Bötticher N, et al. · · 2026 · cited 5 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
T-cell-mediated rejection (TCMR) remains a major cause of kidney transplant failure, despite being considered treatable.
Closing excerpt
Collectively, our results identify epithelial injury cell states as a determinant of outcome after TCMR.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (156 words)

T-cell-mediated rejection (TCMR) remains a major cause of kidney transplant failure, despite being considered treatable. Its impact reflects a limited understanding of the underlying molecular mechanisms and their clinical consequences. To address this, we induced acute TCMR in mouse kidney transplants and profiled molecular changes using single-nucleus RNA sequencing (snRNA-seq), spatial transcriptomics and immunofluorescence. Results were compared with human snRNA-seq data from TCMR and stable allografts, as well as single-cell deconvolution analysis of bulk transcriptomic data from kidney transplant biopsies. Here we show that TCMR induces injured epithelial cell states in mouse kidney allografts, particularly in proximal tubules and thick ascending limbs. Spatial transcriptomics of these injured epithelial states demonstrated heterogeneous localization, interactions with immune cells and cellular microenvironments. Cross-species analysis confirmed similar severely injured epithelial states in human samples, whose abundances correlated with transplant survival and persisted despite TCMR resolution. Collectively, our results identify epithelial injury cell states as a determinant of outcome after TCMR.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41605921 · DOI · PMC12852170

Development and validation of a bronchoalveolar lavage genomic classifier for acute cellular rejection [2]

Research article Weigt SS, Zhou J, Okuno T, Neely ML, Lari S, Palchevskiy V, et al. · · 2025 · cited 5 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
BackgroundAcute cellular rejection (ACR) is the main risk factor for chronic lung allograft dysfunction (CLAD), but diagnosis requires invasive transbronchial biopsy (TBB).
Closing excerpt
FundingThis study was supported by the National Institute of Allergy and Infectious Diseases awards U01AI113315 and U01AI0635594, the Cystic Fibrosis Foundation award PALMER19AB0, and the Saul and Joyce Brandman Foundation Center for Lung Health at UCLA.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (252 words)

BackgroundAcute cellular rejection (ACR) is the main risk factor for chronic lung allograft dysfunction (CLAD), but diagnosis requires invasive transbronchial biopsy (TBB). We previously demonstrated the feasibility of bronchoalveolar lavage cell pellet (BAL-cp) gene expression for ACR diagnosis. We sought to develop and validate a genomic classifier for ACR in a multicenter cohort.MethodsWe performed RNA-seq on 806 BAL-cp from 181 lung transplant recipients enrolled in CTOT-20. Differential expression was based on fold difference >2.0 and False Discovery adjusted p-value FindingsFrom 37 clinically significant ACR and 151 stable control samples, we identified 62 ACR genes, indicating upregulation of T-cell receptor signalling, and downregulation of CTLA4 signalling in cytotoxic lymphocytes, among other enriched pathways. A 31-gene Random Forest model's AUC was 0.99 (SE 0.0053) in the training set, and 0.72 (SE 0.0874) in the test set. At a probability threshold of 0.396, accuracy for distinguishing clinically significant ACR cases from stable controls was 93.1% (specificity 95.4%, sensitivity 83.8%). In the independent validation cohort, accuracy was 82.1% (specificity 87.5%, sensitivity 73.3%). The model classified 138 (17.1%) CTOT-20 samples as genomic ACR. Late genomic ACR (≥90 days posttransplant) associated with increased CLAD risk (HR 2.52, 95% CI 1.47-4.34, p InterpretationA BAL-cp genomic classifier can identify ACR, predict CLAD risk, and may be a less invasive alternative to TBB after lung transplant.FundingThis study was supported by the National Institute of Allergy and Infectious Diseases awards U01AI113315 and U01AI0635594, the Cystic Fibrosis Foundation award PALMER19AB0, and the Saul and Joyce Brandman Foundation Center for Lung Health at UCLA.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41337937 · DOI · PMC12719680

Non-HLA antibody trajectories may predict kidney transplant outcomes [3]

Research article Rajalingam R, Sigdel TK, Maruthamuthu S, Raghav PK, Laszik ZG, Da Gente G, et al. · · 2026 · cited 4 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
IntroductionDonor-specific HLA antibodies (DSAs) are well-established mediators of antibody-mediated rejection (AMR), but growing evidence suggests that non-HLA antibodies may also contribute to kidney allograft dysfunction.
Closing excerpt
Larger multicenter studies are needed to define clinically meaningful threshold and estabilish the utility of non-HLA PRA testing across diverse transplant populations.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (258 words)

IntroductionDonor-specific HLA antibodies (DSAs) are well-established mediators of antibody-mediated rejection (AMR), but growing evidence suggests that non-HLA antibodies may also contribute to kidney allograft dysfunction. However, the clinical utility of non-HLA antibody testing remains limited due to assay variability and undefined pathogenic thresholds.MethodsIn this longitudinal study, we evaluated 167 deceased-donor kidney transplant recipients at UCSF using a multiplex Luminex assay to quantify IgG reactivity against 88 non-HLA antigens in paired pre- and post-transplant serum samples (n = 334). Patients were stratified by HLA-DSA status and graft outcome. The non-HLA panel reactive antibody (PRA) percentage was defined as the proportion of positive beads among the 88 tested antigens.ResultsGlobal non-HLA PRA declined significantly from pre- to post-transplant (9% to 6%; P = 0.0010) only among recipients with functioning grafts, driven by reduced reactivity to signaling, cytoskeletal, and immune-related antigens. Elevated pre-transplant non-HLA PRA was associated with prior sensitization, IgA nephropathy, and African American ancestry, but was independent of age, ABO type, and HLA cPRA. AMR occurred primarily in recipients with both preformed and de novo DSA, while no rejection was observed in DSA-negative recipients. Death-censored graft survival varied across groups, and neither preformed nor de novo DSA consistently predicted outcomes.DiscussionThese findings suggest that longitudinal trajectories of non-HLA PRA, rather than staticmeasurements or DSA status alone, may influence graft loss. The dynamic nature of non-HLA antibody responses and supports integration of non-HLA antibody profiling into longitudinal immune monitoring frameworks. Larger multicenter studies are needed to define clinically meaningful threshold and estabilish the utility of non-HLA PRA testing across diverse transplant populations.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41816322 · DOI · PMC12971436

Key reviews and meta-analyses

The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.

  • Research article Regulatory cell therapy in kidney transplantation (The ONE Study): a harmonised design and analysis of seven non-randomised, single-arm, phase 1/2A trials [4]
    Sawitzki B, Harden PN, Reinke P, Moreau A, Hutchinson JA, Game DS, et al. · Lancet · 2020 · cited 401 times (Europe PMC)
  • Research article Assessing relative risks of infection and rejection: a meta-analysis using an immune function assay [5]
    Kowalski RJ, Post DR, Mannon RB, Sebastian A, Wright HI, Sigle G, et al. · Transplantation · 2006 · cited 245 times (Europe PMC)
  • Research article Corneal neovascularization as a risk factor for graft failure and rejection after keratoplasty: an evidence-based meta-analysis [6]
    Bachmann B, Taylor RS, Cursiefen C · Ophthalmology · 2010 · cited 206 times (Europe PMC)
  • Research article Azathioprine and Risk of Skin Cancer in Organ Transplant Recipients: Systematic Review and Meta-Analysis [7]
    Jiyad Z, Olsen CM, Burke MT, Isbel NM, Green AC · Am J Transplant · 2016 · cited 151 times (Europe PMC)
  • Research article What is the impact of hypogammaglobulinemia on the rate of infections and survival in solid organ transplantation? A meta-analysis [8]
    Florescu DF, Kalil AC, Qiu F, Schmidt CM, Sandkovsky U · Am J Transplant · 2013 · cited 131 times (Europe PMC)
  • Research article The Treatment of Antibody-Mediated Rejection in Kidney Transplantation: An Updated Systematic Review and Meta-Analysis [9]
    Wan SS, Ying TD, Wyburn K, Roberts DM, Wyld M, Chadban SJ · Transplantation · 2018 · cited 117 times (Europe PMC)

References

  1. Pfefferkorn AM, Jahn L, Gauthier PT, Kulow VA, Roeles J, Müller-Bötticher N, et al.. Injured epithelial cell states impact kidney allograft survival after T-cell-mediated rejection. . 2026. PMID 41605921 · DOI · PMC12852170
  2. Weigt SS, Zhou J, Okuno T, Neely ML, Lari S, Palchevskiy V, et al.. Development and validation of a bronchoalveolar lavage genomic classifier for acute cellular rejection. . 2025. PMID 41337937 · DOI · PMC12719680
  3. Rajalingam R, Sigdel TK, Maruthamuthu S, Raghav PK, Laszik ZG, Da Gente G, et al.. Non-HLA antibody trajectories may predict kidney transplant outcomes. . 2026. PMID 41816322 · DOI · PMC12971436
  4. Sawitzki B, Harden PN, Reinke P, Moreau A, Hutchinson JA, Game DS, et al.. Regulatory cell therapy in kidney transplantation (The ONE Study): a harmonised design and analysis of seven non-randomised, single-arm, phase 1/2A trials. Lancet. 2020. PMID 32446407 · DOI · PMC7613154
  5. Kowalski RJ, Post DR, Mannon RB, Sebastian A, Wright HI, Sigle G, et al.. Assessing relative risks of infection and rejection: a meta-analysis using an immune function assay. Transplantation. 2006. PMID 16969290 · DOI
  6. Bachmann B, Taylor RS, Cursiefen C. Corneal neovascularization as a risk factor for graft failure and rejection after keratoplasty: an evidence-based meta-analysis. Ophthalmology. 2010. PMID 20605214 · DOI
  7. Jiyad Z, Olsen CM, Burke MT, Isbel NM, Green AC. Azathioprine and Risk of Skin Cancer in Organ Transplant Recipients: Systematic Review and Meta-Analysis. Am J Transplant. 2016. PMID 27163483 · DOI
  8. Florescu DF, Kalil AC, Qiu F, Schmidt CM, Sandkovsky U. What is the impact of hypogammaglobulinemia on the rate of infections and survival in solid organ transplantation? A meta-analysis. Am J Transplant. 2013. PMID 23919557 · DOI
  9. Wan SS, Ying TD, Wyburn K, Roberts DM, Wyld M, Chadban SJ. The Treatment of Antibody-Mediated Rejection in Kidney Transplantation: An Updated Systematic Review and Meta-Analysis. Transplantation. 2018. PMID 29315141 · DOI

About this article

Sources
NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
Verification
Every reference was resolved against PubMed on 2026-10-31; title, year and DOI matched.
Review state
automated source verified; no human expert review has been recorded yet.
Version
1, last updated 2026-10-29.

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Related research topics

  • Graft SurvivalImmunology
  • Transplantation ToleranceImmunology
  • TransplantsAnatomy and Physiology
  • Lymphocyte ActivationImmunology
  • Graft vs Host DiseaseImmunology
  • Graft vs Host ReactionImmunology

All 90 articles in Immunology →

At a glance

68,521
PubMed records on this heading
12%
published since 2020
10,437
review articles
1,981
randomized trials
9
verified references below

Counts come from PubMed on 2026-10-29; they show how much has been written, not how strong the evidence is.

Related topics See all →

  • Graft SurvivalImmunology
  • Transplantation ToleranceImmunology
  • TransplantsAnatomy and Physiology
  • Lymphocyte ActivationImmunology
  • Graft vs Host DiseaseImmunology

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