Diagnostic value of three urine miRNAs composite score in BK virus nephropathy

IF 2.9 3区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY Clinica Chimica Acta Pub Date : 2025-03-01 Epub Date: 2025-01-25 DOI:10.1016/j.cca.2025.120162
Zhoufan Zhang , Changling Cao , Cuello Garcia Haider , Yinfeng Wang , Yiying Zhu , Ouzaouit Abdelhak , Haitao Liu , Chenzhen Yu , Sheng Chang , Weijie Zhang , Tingya Jiang , Yang Zhou
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Abstract

Noninvasive detection of BK virus, for early detection of BK polyomavirus-associated nephropathy post-renal transplantation, is currently an active subject of investigation. In this study, we developed and validated a novel risk score diagnostic assay (PymiR Score) based on measurements of three urine miRNAs, including BKV-related miRNA (bkv-miR-B1-5p), polyomavirus-related miRNA (bkv-miR-B1-3p) and renal tubular injury-related miRNA (miR-21-5p), by quantitative polymerase chain reaction. The limit of detection of the three miRNAs was 2 × 103 copies/mL, while the intra- and inter-assay coefficients of variation were in the ranges of 2.13 %-3.59 % and 2.30 %-3.35 %, respectively. In the training set, we identified that at a PymiR Score of 71.78, the maximum sensitivity and specificity for the detection of BKVAN were 76.9 % and 100 % respectively, with the receiver-operator characteristic (ROC) analysis showing an area under the curve of 0.8681. In the validation set, we observed a significant difference in the PymiR Score between BKV infection and biopsy-proven BKVAN (P < 0.05), with the ROC analysis showing a sensitivity of 72.73 %, specificity of 100 %, and an AUC of 0.8571. Compared with the area under the ROC curve of plasma BK virus DNA load (AUC = 0.7266), the PymiR Score exhibited higher discrimination capacity (P<0.05) between BKV infection and biopsy-proven BKVAN. Overall, this non-invasive approach offers a robust and convenient alternative for the diagnosis of BK polyomavirus-associated nephropathy.
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三种尿液 miRNAs 综合评分在 BK 病毒性肾病中的诊断价值。
无创检测BK病毒,早期发现肾移植后BK多瘤病毒相关肾病,目前是一个活跃的研究课题。在这项研究中,我们开发并验证了一种新的风险评分诊断方法(PymiR评分),该方法基于三种尿液miRNA的测量,包括bkv相关miRNA (bkv-miR-B1-5p),多瘤病毒相关miRNA (bkv-miR-B1-3p)和肾小管损伤相关miRNA (miR-21-5p),通过定量聚合酶链反应。3种mirna的检出限为2 × 103 copies/mL,测定内变异系数和测定间变异系数分别为2.13 % ~ 3.59 %和2.30 % ~ 3.35 %。在训练集中,我们发现在PymiR评分为71.78时,检测BKVAN的最大灵敏度和特异性分别为76.9% %和100 %,接受者-操作者特征(ROC)分析显示曲线下面积为0.8681。在验证集中,我们观察到BKV感染和活检证实的BKVAN之间的PymiR评分有显著差异(P < 0.05), ROC分析显示敏感性为72.73 %,特异性为100 %,AUC为0.8571。与血浆BK病毒DNA负荷的ROC曲线下面积(AUC = 0.7266)相比,PymiR评分对BKV感染和活检证实的BKVAN具有更高的区分能力(P<0.05)。总的来说,这种非侵入性方法为诊断BK多瘤病毒相关肾病提供了一种强大而方便的替代方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Clinica Chimica Acta
Clinica Chimica Acta 医学-医学实验技术
CiteScore
10.10
自引率
2.00%
发文量
1268
审稿时长
23 days
期刊介绍: The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.
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