ReviewWorld journal of transplantation2016
Proteomics for rejection diagnosis in renal transplant patients: Where are we now?
Review in World journal of transplantation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Urinary Biomarkers for Diagnosis and Prediction of Acute Kidney Allograft Rejection: A Systematic Review.International journal of molecular sciences · 2020Pooled it
- Update on diagnostic and therapeutic strategies for antibody-mediated rejection in kidney transplantation.World journal of transplantation · 2026Review
- Predicting Cellular Rejection of Renal Allograft Based on the Serum Proteomic Fingerprint.International journal of molecular sciences · 2024Article
- Exosomes as Modulators and Biomarkers of Transplant Immunity.Current transplantation reports · 2023Article
- Proteomic analysis investigating kidney transplantation outcomes- a scoping review.BMC nephrology · 2023Article
- Noninvasive Diagnosis of Acute Rejection in Renal Transplant Patients Using Mass Spectrometric Analysis of Urine Samples: A Multicenter Diagnostic Phase III Trial.Transplantation direct · 2022Article
- A Prospective Multicenter Trial to Evaluate Urinary Metabolomics for Non-invasive Detection of Renal Allograft Rejection (PARASOL): Study Protocol and Patient Recruitment.Frontiers in medicine · 2021Article
- Urinary Peptidomic Biomarkers in Kidney Diseases.International journal of molecular sciences · 2019Review
- A urinary metabolite constellation to detect acute rejection in kidney allografts.EBioMedicine · 2019Article
- Advances in Detection of Kidney Transplant Injury.Molecular diagnosis & therapy · 2019Review
- Increased levels of circulating MMP3 correlate with severe rejection in face transplantation.Scientific reports · 2018Article
- GC/MS-based urine metabolomics analysis of renal allograft recipients with acute rejection.Journal of translational medicine · 2018Article
- Non-invasive approaches in the diagnosis of acute rejection in kidney transplant recipients, part II: omics analyses of urine and blood samples.Clinical kidney journal · 2017Review
- Assessment of Circulating Protein Signatures for Kidney Transplantation in Pediatric Recipients.Frontiers in medicine · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rejection is one of the key factors that determine the long-term allograft function and survival in renal transplant patients. Reliable and timely diagnosis is important to treat rejection as early as possible. Allograft biopsies are not suitable for continuous monitoring of rejection. Thus, there is an unmet need for non-invasive methods to diagnose acute and chronic rejection. Proteomics in urine and blood samples has been explored for this purpose in 29 studies conducted since 2003. This review describes the different proteomic approaches and summarizes the results from the studies that examined proteomics for the rejection diagnoses. The potential limitations and open questions in establishing proteomic markers for rejection are discussed, including ongoing trials and future challenges to this topic.
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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.