Evidence map›Paper›PMID 39384354›Full record

ArticleKidney research and clinical practice2025

Donor-derived cell-free DNA-based liquid biopsies to determine future kidney transplant rejection.

Weiwei Wang, Cuello Garcia Haider, Yinfeng Wang, Zhoufan Zhang, Yuelin Liu, Fengcheng Xue, Haitao Liu, Tingya Jiang, Jingyi Cao, Yang Zhou

Abstract read
In one paragraph

Article in Kidney research and clinical practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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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

10 authors.

Weiwei WangCollege of Biology and Food Engineering, Suzhou University, Suzhou, China.
Cuello Garcia HaiderSchool of Life Sciences, Jiangsu University, Zhenjiang, China.
Yinfeng WangSchool of Life Sciences, Jiangsu University, Zhenjiang, China.
Zhoufan ZhangSchool of Life Sciences, Jiangsu University, Zhenjiang, China.
Yuelin LiuSchool of Life Sciences, Jiangsu University, Zhenjiang, China.
Fengcheng XueSchool of Life Sciences, Jiangsu University, Zhenjiang, China.
Haitao LiuBiostatistics, R&D, AlloDx Biotech (Shanghai), Co., Ltd., Shanghai, China.
Tingya JiangBiostatistics, R&D, AlloDx Biotech (Shanghai), Co., Ltd., Shanghai, China.
Jingyi CaoDepartmednt of Urology Surgery, Xuzhou Cancer Hospital, Jiangsu University Affiliated Hospital, Xuzhou, China.
Yang ZhouSchool of Life Sciences, Jiangsu University, Zhenjiang, China.

Funding

Higher Education Science Research Project of Anhui Province 2022AH051362Medicine and Education of Jiangsu University JDY2023020Suzhou Science and Technology Plan Project 2019087
6 · The paper itself

Abstract

Donor-derived cell-free DNA (dd-cfDNA) based liquid kidney biopsies have the potential to detect the chances of kidney transplant rejection. Several studies have found that dd-cfDNA can be used to determine the risk of kidney transplant rejection and may correlate with antibody-mediated rejection (ABMR), T cell-mediated rejection (TCMR), and estimated glomerular filtration rate (eGFR). A high concentration of dd-cfDNA in the body fluids may indicate possible transplant rejection since dd-cfDNA is released as a result of apoptotic and necrotic processes initiated by the recipient's immune system. dd-cfDNA assays have advantages over conventional biopsies since they are noninvasive, and therefore, have the potential to provide a safe and reliable biomarker. Different dd-cfDNA levels have been reported above a number of cutoff thresholds: ABMR at 2.45% and TCMR at 1.3%, compared with 0.44% in healthy patients; and eGFR at 2.5%, a decrease of 25% compared with healthy patients. These results indicate the levels of dd-cfDNA that may be used to signal possible kidney rejection. dd-cfDNA assay is a rapid technique, making it particularly useful in emergencies, and further research into its use in the study of kidney rejection should prove beneficial.

Indexed as

BiomarkersCell-free nucleic acidsGraft rejectionKidney transplantationLiquid biopsy

Identifiers

PMID39384354
PMCPMC12417585

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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.