Evidence map›Paper›PMID 41846918›Full record

ArticleFrontiers in immunology2026

Anti-angiotensin II type 1 receptor autoantibodies of IgG3 subclass outperform total anti-AT1R IgG1-IgG4 levels in predicting transplanted kidney antibody-mediated rejection.

Jakub Mizera, Karolina Marek-Bukowiec, Guido Moll, Rusan Catar, Harald Heidecke, Kai Schulze-Forster, Patryk Jerzak, Mateusz Rakowski, Karolina Władyczak, Agnieszka Hałoń and 3 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

1 citing paper in PubMed.

  1. 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

13 authors.

Jakub MizeraDepartment of Nephrology, Transplantation Medicine and Internal Diseases, Institute of Internal Diseases, Wroclaw Medical University, Wroclaw, Poland.
Karolina Marek-BukowiecDepartment of Nephrology, Transplantation Medicine and Internal Diseases, Institute of Internal Diseases, Wroclaw Medical University, Wroclaw, Poland.
Guido MollBerlin Institute of Health (BIH) Center and School for Regenerative Therapies (BCRT/BSRT), Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health (BIH), Berlin, Germany.
Rusan CatarDepartment of Nephrology and Internal Intensive Care Medicine, Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health (BIH), Berlin, Germany.
Harald HeideckeCellTrend GmbH, Luckenwalde, Germany.
Kai Schulze-ForsterCellTrend GmbH, Luckenwalde, Germany.
Patryk JerzakDepartment of Nephrology, Transplantation Medicine and Internal Diseases, Institute of Internal Diseases, Wroclaw Medical University, Wroclaw, Poland.
Mateusz RakowskiUniversity Clinical Hospital in Wroclaw, Wroclaw, Poland.
Karolina WładyczakUniversity Clinical Hospital in Wroclaw, Wroclaw, Poland.
Agnieszka HałońUniversity Clinical Hospital in Wroclaw, Wroclaw, Poland.
Dariusz JanczakUniversity Clinical Hospital in Wroclaw, Wroclaw, Poland.
Piotr DonizyUniversity Clinical Hospital in Wroclaw, Wroclaw, Poland.
Mirosław BanasikDepartment of Nephrology, Transplantation Medicine and Internal Diseases, Institute of Internal Diseases, Wroclaw Medical University, Wroclaw, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Antibody-mediated rejection (AMR) is a leading cause of kidney allograft loss. Anti-angiotensin II type-1 receptor (AT1R) autoantibodies (AABs) have been implicated in AMR and microvascular inflammation (MVI), particularly in C4d-negative and non-HLA antibody dependent cases. Conventional assays measure only total IgG and do not assess pathogenic subclass heterogeneity. Whether IgG1-IgG4 subclass profiling improves AMR prediction has not yet been investigated. Methods: We included 143 adult kidney-transplant recipients who underwent indication biopsy between 2018 and 2025. Histopathology was classified according to Banff 2017-2022 criteria. Serum samples were analysed for total AT1R-IgG (U/mL) and AT1R IgG1-IgG4 subclasses (relative optical density). Associations with AMR were assessed using group comparisons, correlation analysis, logistic regression, ROC AUC, and quartile-based analyses. Results: AT1R-IgG3 levels were significantly elevated in AMR (Kruskal-Wallis, p = 0.0396), correlated with AMR (Spearman ρ = 0.19, p = 0.02), and demonstrated better predictive performance (AUC 0.63 vs 0.53) than total AT1R-IgG. Logistic regression showed stronger associations for IgG3 (OR 1.33, p = 0.0004) than total AT1R-IgG (OR 1.19, p = 0.029). AMR prevalence increased across IgG3 quartiles (Q1:10.5% → Q4:31.6%), while no such trend was observed for total AT1R-IgG. Conclusions: AT1R antibodies of IgG3 subclass outperform total AT1R levels in predicting AMR, revealing pathogenic antibody patterns that are not detectable through global IgG quantitation. Subclass profiling may contribute to more precise AMR risk assessment, but longitudinal and multicentre validation studies with standardized subclass-specific assays are needed to confirm these findings. Although AT1R IgG3 levels were significantly correlated with AMR, the magnitude of these associations is insufficient to support their use as an independent diagnostic marker and may only serve as a complementary AMR marker.

Indexed as

AutoantibodiesGraft RejectionImmunoglobulin GKidney TransplantationReceptor, Angiotensin, Type 1AdultBiomarkersFemaleHumansMaleMiddle AgedAutoantibodiesBiomarkersImmunoglobulin GReceptor, Angiotensin, Type 1anti-angiotensin II type 1 receptor (AT1R)anti-AT1R-directed functional/regulatory autoantibodies (AT1R-AABs/RABs)antibody-mediated rejection (AMR)Banff classificationG protein-coupled receptors (GPCRs)kidney transplantation (KTx)microvascular inflammation (MVI)non-HLA antibodies

Identifiers

PMID41846918
PMCPMC12989333

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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.