---
title: "Urinary Kidney-Specific Cell-Free DNA Levels in Preeclampsia Compared to Normotensive Controls"
id: "plos-one-23-analysis-of-urinary-kidney-specific-cell-free-dna-in-preeclampsia"
canonical_url: "https://medichelpline.com/clinical-feed/plos-one-23-analysis-of-urinary-kidney-specific-cell-free-dna-in-preeclampsia"
content_type: "clinical_feed_article"
specialty: "General"
source_name: "PLOS ONE (Medicine)"
source_url: "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0359105"
published_at: "2026-09-29T14:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Urinary Kidney-Specific Cell-Free DNA Levels in Preeclampsia Compared to Normotensive Controls
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/plos-one-23-analysis-of-urinary-kidney-specific-cell-free-dna-in-preeclampsia
- **Specialty:** [General](https://medichelpline.com/clinical-feed/general.md)
- **Primary Source:** PLOS ONE (Medicine)
- **Source URL:** [Original Journal Publication](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0359105)
- **Published At:** 2026-09-29T14:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- This study evaluates kidney-specific cell-free DNA (ks-cfDNA) in preeclampsia (PE) vs. normotensive pregnancy (NP). - **Preeclampsia** affects approximately 5% of pregnancies and is characterized by hypertension and organ dysfunction, including renal injury. - Researchers analyzed urine samples from 20 women with PE and 20 matched NP controls, using digital PCR to quantify urinary ks-cfDNA. - **Higher levels** of ks-et2 and ks-et3 were observed in the PE group, indicating **elevated renal injury** markers. - Median ks-et2 was significantly increased in PE (231 copies/mL) vs. NP (62 copies/mL), and ks-et3 was also higher in PE (81 copies/mL vs. 20 copies/mL). - Urinary creatinine levels were 10.9 mmol/L in the PE cohort compared to 3.9 mmol/L in NP, with urine creatinine demonstrating the highest predictive value for PE (AUC 0.76). - Study findings suggest potential of urinary ks-cfDNA as a biomarker for **renal injury** in PE, though more research is required for clinical utility. - The study emphasizes the difficulty in diagnosing PE in women with pre-existing kidney conditions, where standard markers may be misleading.
## Clinical Analysis & Structured Key Points
Analysis of urinary kidney-specific cell-free DNA in preeclampsia | PLOS One Browse Subject Areas ? Click through the PLOS taxonomy to find articles in your field. For more information about PLOS Subject Areas, click here . Article Authors Metrics Comments Media Coverage Reader Comments Figures Figures Abstract Aim To assess the feasibility of a novel methodology for quantifying kidney-specific cell-free DNA (ks-cfDNA) and explore whether levels differed between individuals with preeclampsia (PE) and normotensive pregnant controls (NP). Background Cell-free DNA (cfDNA) is released during cell death and circulates in bodily fluids, including urine. cfDNA quantities reflect the degree of organ injury. As PE is associated with hypertension and kidney injury, we hypothesised that urinary ks-cfDNA would be elevated in PE. Methods In this single-centre prospective case-control study urine samples were collected from 20 women with PE and 20 NP controls. Digital PCR was used to quantify three kidney-specific epigenetic targets (ks-et): ks-et1 (pan-kidney marker), ks-et2 (renal proximal tubular epithelial cell (RPTEC) and podocyte marker) and ks-et3 (RPTEC marker). The beta-actin gene (ACTB) represented total cfDNA (t-cfDNA). Results ks-et2 and ks-et3 were higher in the PE group. Median ks-et2 was 231 copies/mL (IQR 65–383) versus 62 copies/mL (IQR 29–215) in NP controls ( P = 0.028). Median ks-et3 was 81 copies/mL (IQR 28–199) in PE versus 20 copies/mL (IQR 9–81) for NP participants ( P = 0.047). ks-et1 and t-cfDNA showed non-significant increases in PE. Fractional ks-et quantities normalised to t-cfDNA did not differ between groups. Urinary creatinine levels were higher in the PE group (10.9 mmol/L (IQR 4.1–15.3) versus 3.9 mmol/L (IQR 2.3–5.6), P = 0.005). Urine creatinine demonstrated the highest AUC (0.76, 95% CI 0.59–0.92). Conclusion This exploratory study found that quantification of urinary ks-cfDNA was feasible and that absolute quantities of ks-cfDNA markers ks-et2 and ks-et3 were elevated in PE. Consistent with previous studies, urinary creatinine was a good predictor of PE and outperformed ks-cfDNA in discriminating between preeclamptic and normotensive pregnancies. Further studies are needed to determine the clinical utility and predictive ability of ks-cfDNA in PE. Citation: Heron VC, Whitlam JB, Murray DH, Boulter N, Mount P, Choy S-W, et al. (2026) Analysis of urinary kidney-specific cell-free DNA in preeclampsia. PLoS One 21(9): e0359105. https://doi.org/10.1371/journal.pone.0359105 Editor: Maria Lourdes Gonzalez Suarez, Mayo Clinic Rochester, UNITED STATES OF AMERICA Received: May 24, 2026; Accepted: September 9, 2026; Published: September 29, 2026 Copyright: © 2026 Heron et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: The minimal data set is available at Melbourne Figshare via https://doi.org/10.26188/32353551 . Funding: VCH was supported by Jacquot Research Entry Scholarships from The Royal Australasian College of Physicians Foundation and the late Don and Lorraine Jacquot (2022RES00054 and 2023RES 00139) [ https://www.racp.edu.au/foundation/research-awards-and-careergrants/about/jacquot-awards ]. VCH was supported by the Commonwealth through an Australian Government Research Training Program Scholarship [DOI: https://doi.org/10.82133/C42F-K220 ]. KP was supported by a grant from the Austin Medical Research Foundation (G J 2002824 AMRF) [ https://www.austinmrf.org.au/ ]. Sysmex R&D Centre Europe GmbH provided support in the form of a salary for DHM but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of this author is articulated in the ‘author contributions’ section. Funders and sponsors did not play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests. DHM and NB have a patient for the kidney diagnostic PCT/AU2023/050562, filed on 21 June 2023 entitled, “Detection of cell damage,” which claims priority to Australian provisional patent application number 2022901697, filed on 21 June 2022. DHM is an employee of Sysmex R&D Centre Europe GmbH and provided support in the form of a salary for DHM. The company did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. This does not alter our adherence to PLOS ONE policies on sharing data and materials. Introduction Preeclampsia (PE) affects 5% of pregnant women after 20 weeks’ gestation and is characterised by new-onset hypertension and multi-organ dysfunction, including kidney involvement [ 1 ]. While proteinuria and acute kidney injury are common manifestations of the kidney injury in PE, the pathogenetic mechanisms underlying these kidney changes remain incompletely understood [ 2 ]. In women with pre-existing kidney disease and/or hypertension, diagnosing PE can be challenging. Furthermore, standard measures of kidney health (serum creatinine and urine protein-to-creatinine ratio (uPCR)) are altered in pregnancy and not predictive of clinical disease onset. Cell-free DNA (cfDNA) is an extracellular nucleic acid present in bodily fluids including blood and urine [ 3 ]. cfDNA in the plasma is primarily derived from the demise of leukocytes [ 4 ]. A small amount of cfDNA originates from solid organs and, in cases of organ injury or damage, the quantity of cfDNA increases [ 5 ]. Cell-free DNA has a short half-life of two minutes to two hours, allowing for real-time analysis of pathological processes associated with cfDNA release [ 6 ]. In transplantation, there is an established association between donor-derived cfDNA (dd-cfDNA) released from the allograft and pathology affecting that organ [ 7 ]. Similar to antibody-mediated rejection in transplanted organs, PE is associated with glomerular endothelial injury. Unlike the transplant context, where genetic polymorphisms between individuals can be used to distinguish dd-cfDNA from recipient cfDNA, in a non-chimeric individual this is not possible. Therefore, this study used kidney-specific epigenetic markers to distinguish kidney-specific cfDNA (ks-cfDNA) from total cfDNA. Beyond transplantation and organ injury, cfDNA has been extensively studied in pregnancy-related contexts. Fetal circulating cfDNA was first reported in 1997 and is now commonly used in the maternity setting for non-invasive prenatal diagnosis [ 8 ]. In the search for a biomarker predictive of PE in early pregnancy, cfDNA has been investigated. Total maternal circulating cfDNA has been found to be higher in women with PE compared to those with normotensive pregnancies or isolated fetal growth restriction [ 9 ]. Furthermore, a lower fetal fraction of circulating cfDNA has been reported to be predictive of PE [ 10 ]. cfDNA is also detectable in the urine. Urinary cfDNA originates from two primary sources. Firstly, circulating cfDNA is filtered into the urine by the glomeruli. Secondly, cfDNA is released directly into the urinary filtrate by kidney and urinary tract cells [ 11 ]. The nephron comprises various cell types, each with its own unique epigenetic signature [ 12 ]. The proportion of ks-cfDNA originating from each cell type is hypothesised to vary in health and disease. Urinary cfDNA has been studied as a biomarker for kidney disease [ 4 , 11 , 13 – 15 ]. While studies have examined the presence of fetal cfDNA in maternal urine, there is currently no published literature examining changes to ks-cfDNA in women with PE [ 16 , 17 ]. This exploratory study aimed to assess the feasibility of a novel methodology for quantifying urinary ks-cfDNA and the biological plausibility of its use as a biomarker, while also exploring whether levels differed between individuals with PE and normotensive pregnant controls (NP). We hypothesized that PE is associated with elevated levels of ks-cfDNA, reflecting renal injury. Methods Study design This single-centre, prospective, case-control study was granted approval by the Mercy Health Human Research Ethics Committee (2022−018). Women were recruited from the Mercy Hospital for Women, Heidelberg, Australia between March and October 2023. Urine samples were collected from 20 women after diagnosis of PE and 20 NP controls, matched by gestational age. Inclusion criteria were adult participants more than 20 weeks gestation giving written informed consent. PE was defined as per the 2023 Society of Obstetric Medicine of Australia and New Zealand (SOMANZ) diagnostic criteria [ 18 ]. PE with severe features was defined according to the American College of Obstetricians and Gynecologists (ACOG) criteria, as severity classification is not incorporated into the relevant SOMANZ guideline [ 19 ]. Women were excluded from the NP control group if they had pre-existing hypertension, chronic kidney disease (CKD), or known fetal growth restriction at the time of screening. Demographic and clinical data were collected from the participant and electronic medical record. Kidney-specific epigenetic targets As described by Murray et al., using data generated by Illumina Infinium HumanMethylation450 (450K) or Human MethylationEPIC (EPIC) BeadChip arrays, a human methylation atlas was constructed from a repository of blood and solid tissue samples. Using this pipeline, kidney-specific DNA methylation CpG sites were identified and filtered to three differentially methylated regions (DMRs) across three genes. These DMRs were subsequently developed into PCR targets for a multiplexed digital PCR (dPCR) assay [ 20 ]. For the present study we have referred to each gene as a kidney-specific epigenetic target (ks-et). These genes are: ks-et1: Paired box gene 2 ( PAX2 ), a pan-kidney cell epigenetic marker; ks-et2: Gram domain containing 1B ( GRAMD1B ), a renal proximal tubular epithelial cell (RPTEC) and podocyte epigenetic marker; and ks-et3: Dopa decarboxylase ( DDC ), a specific RPTEC epigenetic marker. The ks-cfDNA assay was validated using plasma samples from a kidney transplant cohort [ 20 ]. Its performance for urinary ks-cfDNA was subsequently evaluated in an independent cardiac transplantation cohort comprising 10 cardiac transplant recipients who underwent serial postoperative urine sampling, including participants who developed postoperative kidney injury [ 21 ]. This cohort also included non-transplant comparator groups. Detailed clinical findings from this study will be reported separately [Murray et al., manuscript in preparation]. Total cell-free DNA quantification The beta-actin ( ACTB ) gene was used as a non-kidney specific positive control reflecting total cfDNA (t-cfDNA) and was targeted in a separate reaction. ACTB DNA is present in all nucleated cells, is understood to be biallelic and independent of methylation status. It has been widely used as a reference gene in other methylation assays due to its stable expression [ 22 ]. ACTB concentrations were used as a denominator to calculate the percentage of total cfDNA that was ks-cfDNA from an epigenetic target (%ks-et). Assays that had less than three positive partitions were considered below the lower limit of quantification. Sample collection, cfDNA extraction and ks-cfDNA quantification Participants self-collected a mid-stream urine sample which was subsequently cooled to 4°C and centrifuged at 1600x g for 10 minutes as soon as practical. The time between collection and centrifugation of urine ranged from 5 minutes to 3 hours 30 minutes. Urine supernatant was aliquoted and at least 10mL of urine was stored at −80°C. cfDNA was extracted from 4mL of urine using the QIAamp Circulating Nucleic Acid Kit and bisulfite converted using the EpiTect Fast Bisulfite Conversion Kit. 15μl of the volume eluant (equivalent to 1mL urine) was analysed by digital PCR (dPCR) using the QIAcuity Four (Qiagen) platform. Quantification of each ks-et was performed. Biomarker concentrations were normalised to urine creatinine. Laboratory personnel were not blinded to case/control status. The principal laboratory procedures and kidney-specific methylation assays were consistent between the cardiac transplantation cohort and the present pregnancy cohorts. Urine collection and pre-analytical handling differed between the cardiac transplantation and present cohorts. In the cardiac transplantation cohort, urine was collected with Streck urine stabilisation reagent to permit delayed processing. In the present pregnancy cohort, participants provided self-collected mid-stream urine without cfDNA preservative but were centrifuged as soon as possible to minimise post-collection cellular lysis and cfDNA degradation. Statistical analysis GraphPad Prism (version 10.0.2) was used for group comparisons and correlation analyses. Continuous variables were assessed for normality prior to analysis. Demographic variables were compared using an unpaired t-test with Welch’s correction, while categorical variables were compared using Fisher’s exact test. The Mann-Whitney U test was used to compare non-normally distributed values, including ks-et, t-cfDNA, %ks-et and urine creatinine. Spearman’s rank correlation coefficient (ρ) was used to assess relationships between biomarkers, including correlations between ks-et biomarkers, t-cfDNA, urine creatinine, total urinary protein concentration, and available clinical variables. Receiver operating characteristic (ROC) curves were constructed to evaluate the discriminatory performance of each biomarker and urine creatinine for PE. Area under the curve (AUC) values and 95% confidence intervals (CI) were calculated using the DeLong method. Optimal diagnostic thresholds were identified using Youden’s index. To assess whether urine creatinine contributed independent discriminative ability beyond the ks-et biomarkers, a multivariable logistic regression model was fitted with PE as the binary outcome and ks-et1, ks-et2, and ks-et3 as covariates. A second model additionally included urine creatinine. The incremental value of urine creatinine was assessed using a likelihood ratio test comparing the two nested models. ROC and regression analyses were performed in R (version 4.6.0) using the pROC package for ROC analysis. P values 0.8) ( Fig 2e – 2g ). Sensitivity analysis excluding PE participants with pre-existing hypertension In a sensitivity analysis excluding the five PE participants with pre-existing hypertension, the differences in ks-et2 and k
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