ArticleTransplantation direct2020
Urinary Cell Transcriptome Profiling and Identification of ITM2A, SLAMF6, and IKZF3 as Biomarkers of Acute Rejection in Human Kidney Allografts.
Article in Transplantation direct, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Urinary CXCL-10, a prognostic biomarker for kidney graft injuries: a systematic review and meta-analysis.BMC nephrology · 2024Pooled it
- The emerging roles of ITM2A: At the molecular crossroads of development and pathogenesis.iScience · 2026Review
- Benchmarking urinary cell transcriptomes for noninvasive differentiation of BK polyomavirus-associated nephropathy from T cell-mediated rejection.JCI insight · 2026Article
- Endometrial regeneration cell-derived exosomes loaded with siSLAMF6 inhibit cardiac allograft rejection through the suppression of desialylation modification.Cellular & molecular biology letters · 2024Article
- Expression of Rejection-Associated Transcripts in Early Protocol Renal Transplant Biopsies Is Associated with Tacrolimus Exposure and Graft Outcome.International journal of molecular sciences · 2024Article
- Identification of Genes Associated with Decreasing Abundance of Monocytes in Long-Term Peritoneal Dialysis Patients.International journal of general medicine · 2023Article
- Applications of Transcriptomics in the Research of Antibody-Mediated Rejection in Kidney Transplantation: Progress and Perspectives.Organogenesis · 2022Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
Abstract
Identification of a shared gene expression pattern between T cell-mediated rejection (TCMR) and antibody-mediated rejection (AMR) in human kidney allografts may help prioritize targets for the treatment of both types of acute rejection.
methodsWe performed RNA sequencing and bioinformatics of genome-wide transcriptome profiles of urinary cells to identify novel mRNAs shared between TCMR and AMR and of mechanistic relevance. Customized RT-QPCR assays were then used to validate their abundance in urinary cells. Urinary cell transcriptome profiles and mRNA abundance were assessed in 22 urine samples matched to 22 TCMR biopsies, 7 samples matched to 7 AMR biopsies, and 24 samples matched to 24 No Rejection (NR) biopsies and correlated with biopsy diagnosis.
resultsRNA sequencing data and bioinformatics identified 127 genes in urine to be shared between TCMR and AMR. We selected 3 novel mRNAs-ITM2A, SLAMF6, and IKZF3-for absolute quantification and validation by customized RT-QPCR assays. The abundance of all 3 mRNAs was significantly higher in urine matched to TCMR or AMR than in urine matched to NR biopsies. Receiver-operating-characteristic curve analysis showed that all 3 mRNAs distinguished TCMR or AMR from NR. Their abundance was similar in patients with TCMR and those with AMR.
conclusionsState-of-the-art antirejection therapies are mostly effective to treat TCMR but not AMR. Our identification of mRNAs shared between TCMR and AMR and contributing to T cell-B cell interactions may help prioritize therapeutic targets for the simultaneous treatment of TCMR and AMR.
Identifiers
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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.