Evidence map›Paper›PMID 40630324›Full record

ArticleKidney international reports2025

Identification and Cross-Platform Validation of Sparse Molecular Classifiers for Antibody-Mediated and T-Cell-Mediated Rejection After Kidney Transplantation.

Jasper Callemeyn, Josué Manik Nava-Sedeño, Dany Anglicheau, Jack Beadle, Jan Hinrich Bräsen, Marian C Clahsen-van Groningen, Iacopo Cristoferi, Henriette de Loor, Andreas Deutsch, Marie Essig and 13 more

Registry-linked trialAbstract read
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In one paragraph

Article in Kidney international reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01299168 (Multi-centric Observational Study to Analyse the Diagnostic Molecular Features in the Clinical Setting of Kidney Allograft Biopsies), which is not on this map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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.

NCT01299168 recruitingnot on this map

Multi-centric Observational Study to Analyse the Diagnostic Molecular Features in the Clinical Setting of Kidney Allograft Biopsies

TypeobservationalSponsorUniversity of AlbertaRan2011 to 2028Enrolled500ConditionsValidation Study of Molecular Diagnostic System, Development of Reporting System for Molecular Diagnosis, Incorporate Molecular Diagnosis Into Diagnostic Standards
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

23 authors.

Jasper CallemeynNephrology and Renal Transplantation Research Group, Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium.
Josué Manik Nava-SedeñoZentrum für Informationsdienste und Hochleistungsrechnen, Innovative Methods of Computing, Technische Universität Dresden, Dresden, Germany.
Dany AnglicheauUniversité de Paris, Paris, France.
Jack BeadleCentre for Inflammatory Disease, Department of Immunology and Inflammation, Imperial College, London, UK.
Jan Hinrich BräsenNephropathology Unit, Institute of Pathology, Hannover Medical School, Hannover, Germany.
Marian C Clahsen-van GroningenDepartment of Pathology and Clinical Bioinformatics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Iacopo CristoferiDepartment of Pathology and Clinical Bioinformatics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Henriette de LoorNephrology and Renal Transplantation Research Group, Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium.
Andreas DeutschZentrum für Informationsdienste und Hochleistungsrechnen, Innovative Methods of Computing, Technische Universität Dresden, Dresden, Germany.
Marie EssigAP-HP Paris Saclay, Ambroise Pare Hospital, Department of Nephrology, Boulogne Billancourt, France.
Wilfried GwinnerNephrology, Internal Medicine, Hannover Medical School, Hannover, Germany.
Philip F HalloranDepartment of Medicine, Division of Nephrology and Transplant Immunology, University of Alberta, Edmonton, Alberta, Canada.
Dennis A HesselinkErasmus MC Transplant Institute, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Priyanka KoshyDepartment of Morphology and Molecular Pathology, University Hospitals Leuven, Leuven, Belgium.
Dirk KuypersNephrology and Renal Transplantation Research Group, Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium.
Evelyne LerutDepartment of Morphology and Molecular Pathology, University Hospitals Leuven, Leuven, Belgium.
Pierre MarquetPharmacology and Transplantation, INSERM U1248, CHU Limoges, Université de Limoges, Limoges, France.
Robert C MinneeErasmus MC Transplant Institute, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Candice RoufosseCentre for Inflammatory Disease, Department of Immunology and Inflammation, Imperial College, London, UK.
Ben SprangersDepartment of Nephrology and Renal Transplantation, University Hospitals Leuven, Leuven, Belgium.
Amaryllis H Van CraenenbroeckNephrology and Renal Transplantation Research Group, Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium.
Haralampos HatzikirouZentrum für Informationsdienste und Hochleistungsrechnen, Innovative Methods of Computing, Technische Universität Dresden, Dresden, Germany.
Maarten NaesensNephrology and Renal Transplantation Research Group, Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Molecular classifiers are a promising tool to refine the diagnosis of antibody-mediated rejection (ABMR) and T-cell-mediated rejection (TCMR) after kidney transplantation. Despite this potential, the integration of molecular classifiers in transplant clinics has been slow, in part because of the complexity of current assays and lack of a consensus platform. Herein, we aimed to develop and validate sparse molecular classifiers for ABMR and TCMR using allograft tissue. Methods: In a discovery cohort of 224 kidney transplant biopsies, lasso regression was applied on microarray gene expression data to derive a molecular classifier for ABMR and TCMR, respectively. Results: A 2-gene classifier for ABMR ( Conclusion: Rigid variable selection strategies can yield sparse molecular classifiers for allograft rejection phenotypes with preserved accuracy and prognostic value across different molecular diagnostic platforms, which may facilitate their interpretation and clinical implementation.

Indexed as

antibody-mediated rejectiondiagnosisgene expressionkidney transplantationT-cell–mediated rejectiontranscriptomics

Identifiers

PMID40630324
PMCPMC12231026

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Registered trials

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.