Analysis of urine cell-free DNA copy number and fragment size from healthy individuals

IF 2.9 3区医学 Q2 MEDICAL LABORATORY TECHNOLOGY

Clinica Chimica Acta Pub Date : 2025-09-23 DOI:10.1016/j.cca.2025.120627

Jufen Wang , Zilong Wu , Bingyu Wu , Xinghao Lin , Wenhe Wu , Jun Li

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引用次数: 0

Abstract

Objective

This study characterizes urine cell-free DNA (cfDNA) copy number and fragment size in healthy individuals and explores their associations with routine clinical parameters.

Methods

Sixty healthy subjects were enrolled, providing paired blood and urine samples. Six primer pairs targeting nuclear (GAPDH-61/168/241) and mitochondrial DNA (ND1-57/167/240) were designed for absolute qPCR. Optimal urine collection, pre-treatment, and cfDNA detection protocols were evaluated. Correlations between cfDNA characteristics (fragment size and copy number) and clinical parameters (complete blood count, urinalysis, hepatic/renal function biomarkers) were analyzed.

Results

Non-extracted urine retained a higher proportion of fragments < 100 bp and > 2000 bp than extracted samples. The optimal pre-treatment involved immediate EDTA addition, centrifugation at 4°C, and storage at −80°C. Urine cfDNA comprised short, medium, and long fragments. Cell-free mitochondrial DNA (cf-mtDNA) showed the highest copy numbers in short fragments, decreasing with length, whereas cell-free nuclear DNA (cf-nDNA) peaked in medium fragments. ND1-57 Cq values correlated negatively with neutrophil percentage (P < 0.01) and positively with lymphocyte percentage (P < 0.05). Lymphocyte percentage was moderately correlated with ND1 short fragment (ND1-S, P < 0.01) and weakly with the ND1-S to ND1 medium fragment (ND1-M) ratio (P < 0.05). Absolute lymphocyte count correlated weakly with ND1-S (P < 0.01) and ND1-M (P < 0.05). Neutrophil percentage correlated weakly with ND1-S (P < 0.01) and ND1-S to ND1 long fragment (ND1-L) ratio (P < 0.05).

Conclusion

Urine cfDNA displays three distinct fragment sizes, with cf-mtDNA predominantly found in short fragments and showing stronger associations with physiological parameters than cf-nDNA.

查看原文本刊更多论文

健康人尿无细胞DNA拷贝数和片段大小分析。

目的：研究健康人尿游离DNA （cfDNA）拷贝数和片段大小的特征，并探讨其与常规临床参数的关系。方法：选取60名健康受试者，提供配对血液和尿液样本。设计了6对引物，分别针对细胞核（GAPDH-61/168/241）和线粒体DNA （ND1-57/167/240）进行绝对定量pcr。评估最佳尿液收集、预处理和cfDNA检测方案。分析cfDNA特征（片段大小和拷贝数）与临床参数（全血细胞计数、尿液分析、肝肾功能生物标志物）之间的相关性。结果：未提取的尿液中残留的碎片比例 2000 bp高于提取的尿液。最佳的预处理是立即添加EDTA， 4 °C离心，-80 °C保存。尿液cfDNA由短、中、长片段组成。无细胞线粒体DNA （cf-mtDNA）在短片段中拷贝数最多，随长度的增加而减少，而无细胞核DNA （cf-nDNA）在中片段中拷贝数最多。ND1-57 Cq值与中性粒细胞百分比呈负相关（P ）结论：尿cfDNA有三种不同的片段大小，cf-mtDNA以短片段为主，与生理参数的相关性较cf-nDNA强。

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 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.