Evaluation of Total Circulating Cell-Free DNA as a Biomarker in Liver Transplant Recipients: A Single-Center Pilot Study

Evaluation of Total Circulating Cell-Free DNA as a Biomarker in Liver Transplant Recipients: A Single-Center Pilot Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Evaluation of Total Circulating Cell-Free DNA as a Biomarker in Liver Transplant Recipients: A Single-Center Pilot Study Monika Kolanowska, Jakub Franke, Anna Wójcicka, Karolina Wronka, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7077786/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Donor-derived cell-free DNA (dd-cfDNA) has shown promise as a sensitive non-invasive biomarker of graft injury following liver transplantation (LT). This pilot study assessed whether total cfDNA levels alone could reflect liver graft health and predict rejection events. To analyze this, 70 adult LT recipients were stratified by underlying liver disease etiology and monitored for 18 months. Total cfDNA was extracted from plasma samples collected 10 days post-LT and quantified fluorometrically. Associations between cfDNA levels and standard liver function biomarkers (ALT, AST, ALP or tacrolimus dosing) were analyzed using Kendall’s Tau. Differences in cfDNA levels among disease etiologies were assessed using the Kruskal-Wallis test. Median cfDNA concentration was 11 ng/ml (range: <3–70 ng/ml). Highest concentrations were noted in patients with autoimmune liver disease or hepatocellular carcinoma. No significant correlation was observed between cfDNA and ALT, AST, ALP, or tacrolimus levels. A subset of patients with cfDNA ≥ 20 ng/ml (n = 21) showed a moderate correlation with ALT (Tau = 0.46, p = 0.0105). cfDNA levels did not differ between etiological groups. These findings suggest that while total cfDNA reflects some inflammatory activity, it lacks the specificity of dd-cfDNA in clinical transplant monitoring. Larger studies and fraction-specific analysis are warranted. Health sciences/Biomarkers Health sciences/Diseases Health sciences/Gastroenterology Health sciences/Medical research liver transplantation cell-free DNA biomarker graft rejection dd-cfDNA Introduction Liver transplantation (LT) remains the definitive treatment for end-stage liver disease. In 2024, over 600 liver transplants were performed in Poland alone [ 1 ]. Despite advancements, post-transplant monitoring largely relies on liver function tests (LFTs), including ALT, AST, bilirubin, gamma-glutamyl transferase, and ALP [ 2 ]. However, these markers are neither highly specific nor immediate indicators of graft injury. Liver biopsy remains the gold standard for rejection diagnosis, but its invasiveness and delayed turnaround necessitate alternative biomarkers [ 3 ]. Circulating cell-free DNA (cfDNA), first described in 1948 [ 4 ], has since gained relevance in oncology [ 5 ], prenatal medicine [ 6 ], and transplantology [ 7 , 8 ]. Donor-derived cfDNA (dd-cfDNA) has been especially promising in detecting subclinical rejection [ 1 , 9 , 10 ]. Its short half-life (16 minutes to 2.5 hours) enables real-time monitoring [ 11 , 12 ]. However, dd-cfDNA assays require genotyping and are cost-prohibitive for routine use. This study explored whether total cfDNA, regardless of origin, could serve as an accessible biomarker to complement standard LFTs in early detection of graft dysfunction. Materials and Methods Ethical Approval : The study was approved by the Bioethics Committee of the Medical University of Warsaw (KB/186/2021). Written informed consent was obtained from all participants. Study Group : Seventy LT recipients (aged 20–74) were stratified by underlying liver disease: alcohol-induced (n=13), autoimmune (n=20), viral (HBV/HCV, n=9), cancer (HCC/cholangiocarcinoma, n=10), and others (n=18). Detailed group demographics are provided in Table 1. Sample Collection and Processing : Peripheral blood (5 ml) was collected into K3 EDTA tubes 10 days post-LT and processed at 4°C. Plasma was separated via dual centrifugation and stored at -80°C. cfDNA was extracted using the Cobas® cfDNA Sample Preparation Kit (Roche) and analyzed using the Quantus fluorometer (Promega). Fragment size was verified using the Agilent TapeStation system. Data Analysis : Non-parametric statistical methods were employed. Kendall’s Tau was used to assess correlations between cfDNA and ALT, AST, ALP, and tacrolimus trough levels. The Kruskal-Wallis test evaluated cfDNA differences across liver disease groups. Significance was set at p<0.05. All methods were performed in accordance with the relevant guidelines and regulations Results Total cfDNA was successfully extracted from all 70 patients. Median concentration was 11 ng/ml. Three patients (autoimmune and cancer groups) had peak levels of 70 ng/ml. Five patients exhibited cfDNA levels <3 ng/ml, notably excluding the cancer group. No significant associations were found between cfDNA levels and standard clinical parameters. Specifically, Kendall’s Tau correlation analysis did not demonstrate any statistically significant relationships between cfDNA concentration and commonly used blood biomarkers, including alanine aminotransferase (ALT) (Tau = -0.085, p = 0.390), aspartate aminotransferase (AST) (Tau = -0.0594, p = 0.547), and alkaline phosphatase (ALP) (Tau = -0.049, p = 0.616). Similarly, no significant correlation was found between cfDNA levels and tacrolimus dosage (Tau = 0.063, p = 0.519). These results are summarized in Table 2. Furthermore, to explore whether cfDNA levels varied among different liver disease etiologies, a Kruskal–Wallis test was conducted. This analysis also did not reveal any statistically significant differences across the etiological subgroups ( p = 0.29), as presented in Table 3. In a subgroup analysis of 21 patients with cfDNA ≥20 ng/ml, a moderate correlation was observed between cfDNA and ALT (Tau = 0.46, p = 0.0105), though clinical relevance remains unclear. Discussion Recent studies have demonstrated that cell-free DNA (cfDNA) is a sensitive and specific biomarker for early detection of various pathological processes [6, 13-15]. It has been successfully implemented in diagnostic applications across multiple disciplines, including oncology [11, 13], prenatal testing [16], and transplant medicine ([10, 12, 17-20]. Two main characteristics make cfDNA a particularly promising biomarker: its rapid increase in response to inflammatory stimuli and its tissue-specific origin, allowing for potential discrimination between donor- and recipient-derived fractions [21]. In the context of solid organ transplantation, donor-derived cfDNA (dd-cfDNA) has been extensively studied as an early indicator of graft injury. It has been shown to increase in response to both acute rejection and infectious complications [10]. A prospective, multicenter study conducted in German transplant centers confirmed that dd-cfDNA monitoring enables earlier and more sensitive detection of acute rejection compared to standard liver function tests (LFTs) [22]. In another study, Japanese researchers monitored cfDNA and dd-cfDNA levels in 91 liver transplant recipients over a 30-day period. Using 300 single nucleotide polymorphisms (SNPs) for discrimination, they demonstrated high prognostic accuracy of dd-cfDNA for graft injury [23]. Similarly, a pediatric study reported an area under the curve (AUC) greater than 0.84 for cfDNA-based rejection detection, outperforming traditional biomarkers [16]. Moreover, a pilot trial involving 59 patients revealed that cfDNA levels rose before abnormalities in LFTs became evident, suggesting earlier detection of graft dysfunction [24]. Building on these findings, the present study aimed to evaluate whether total cfDNA, measured without fractionating donor-derived components, could serve as a rapid and accessible biomarker for liver graft injury. The test protocol was designed to deliver results within approximately three hours, making it potentially feasible for use in routine clinical laboratories. However, our findings did not show statistically significant correlations between total cfDNA levels and traditional liver biomarkers such as ALT, AST, and ALP. Likewise, no significant association was observed between cfDNA concentration and tacrolimus dosing, nor were cfDNA levels significantly different among patients with various liver disease etiologies (Tables 2–3). These results highlight the complex biological nature of cfDNA dynamics. Unlike dd-cfDNA, which directly reflects graft cell turnover, total cfDNA includes DNA fragments originating from multiple tissues and may be influenced by systemic inflammation, surgical trauma, or other non-specific factors. The absence of statistically significant correlations may reflect this lack of specificity. Notably, in a subgroup of patients with the highest cfDNA concentrations, a moderate correlation with ALT was observed. Given that ALT is regarded as the most specific enzymatic indicator of hepatocellular damage [25], this observation could reflect subclinical graft injury not captured by standard LFTs. Elevated cfDNA concentrations have previously been associated with increased risk of acute rejection [26, 27], supporting the relevance of this signal, though longitudinal data and histological confirmation would be required for validation. Recent literature further supports the superiority of dd-cfDNA over total cfDNA. dd-cfDNA has been shown to correlate well with biopsy-confirmed rejection and typically increases earlier than conventional biomarkers [17, 20]. Moreover, novel approaches are under development. For example, quantification of mitochondrial cfDNA (mt-cfDNA) during ex vivo machine perfusion has demonstrated correlation with post-transplant liver function, offering a promising tool for organ viability assessment [21]. Similarly, epigenetic analyses of cfDNA, particularly methylation-based profiling, may enhance specificity by distinguishing hepatocyte-derived fragments from those of cholangiocyte or non-hepatic origin [10]. Despite these advances, dd-cfDNA testing has not yet been widely implemented in routine clinical practice. As of 2024, the American Society of Transplant Surgeons (ASTS) does not recommend routine dd-cfDNA surveillance post-liver transplantation due to insufficient high-level evidence (ASTS Position Statement, 2024) [28]. Nevertheless, ongoing prospective trials and technological improvements are likely to facilitate broader clinical adoption in the future. Total cfDNA, while less specific, remains attractive for its simplicity, low cost, and fast turnaround time. It may have particular value in resource-limited settings or as an initial triage tool to identify patients requiring further evaluation using more complex dd-cfDNA-based assays. Future studies should consider incorporating cfDNA kinetics, fragmentation patterns, and epigenetic features to enhance diagnostic accuracy without requiring full genotyping. Limitations of the current study include the small sample size, single time-point sampling, and lack of histological validation of graft injury. Inter-patient variability in cfDNA kinetics and clearance, as well as concurrent systemic inflammation, may also have influenced the results. Nonetheless, the feasibility of the method and the observed trends support further investigation. Conclusions Total cfDNA quantification is feasible and logistically simple, but does not demonstrate sufficient sensitivity or specificity to serve as a standalone marker for liver graft injury. Its role may lie in early screening or as part of a multi-analyte biomarker panel. Donor-derived cfDNA remains the more promising candidate for early detection of transplant rejection. Further large-scale, longitudinal studies are needed to validate cfDNA-based monitoring strategies and to refine their clinical applicability. Declarations Author Contribution All the authors (MK, JF, AW, KW, MW, OK, MK, JR-W) contributed to the experimental design, interpretation of the results, drafting of the manuscript and its final approval. MK performed experiments and JF contributed to data analysis. The main person responsible for the drafting of the manuscript was J R-W. Data Availability Data is provided within the manuscript References Centrum Organizacyjno-. Koordynacyjne do Spraw Transplantacji. Statystyka 2024 – POLTRANSPLANT. (pdf). Perottino, G., Harrington, C. & Levitsky, J. Biomarkers of rejection in liver transplantation. Curr. Opin. Organ. Transpl. 27 , 154–158 (2022). Raszeja-Wyszomirska, J. et al. Free-circulating nucleic acids as biomarkers in patients after solid organ transplantation. Ann. Transpl. 28 , e939750 (2023). Mandel, P. & Metais, P. Nuclear acids in human blood plasma. C R Seances Soc. Biol. Fil . 142 , 241–243 (1948). Stawski, R. et al. Current trends in cell-free DNA applications. Scoping review of clinical trials. Biology (Basel . 10 , 9 (2021). Lo, Y. M. D., Han, D. S. C., Jiang, P. & Chiu, R. W. K. Epigenetics, fragmentomics, and topology of cell-free DNA in liquid biopsies. Science 372, 6538 (2021). Bloom, R. D. et al. Cell-free DNA and active rejection in kidney allografts. J. Am. Soc. Nephrol. 28 , 2221–2232 (2017). Rahat, B. et al. Circulating cell-free nucleic acids as epigenetic biomarkers in precision medicine. Front. Genet. 11 , 844 (2020). Baumann, A. K. et al. Elevated fractional donor-derived cell-free DNA during subclinical graft injury after liver transplantation. Liver Transpl. 28 , 1911–1919 (2022). Knight, S. R., Thorne, A. & Lo Faro, M. L. Donor-specific cell-free DNA as a biomarker in solid organ transplantation: a systematic review. Transplantation 103, 273–283 (2019). Bronkhorst, A. J., Ungerer, V. & Holdenrieder, S. The emerging role of cell-free DNA as a molecular marker for cancer management. Biomol. Detect. Quantif . 17 , 100087 (2019). Kataria, A., Kumar, D. & Gupta, G. Donor-derived cell-free DNA in solid-organ transplant diagnostics: indications, limitations, and future directions. Transplantation 105, 1203–1211 (2021). Jamshidi, A. et al. Evaluation of cell-free DNA approaches for multi-cancer early detection. Cancer Cell. 40 , 1537–1549e12 (2022). Zhou, M. et al. Circulating organ-specific microRNAs serve as biomarkers in organ-specific diseases: implications for organ allo- and xeno-transplantation. Int. J. Mol. Sci. 17 , 8 (2016). Zhu, X. et al. Sequencing data of cell-free DNA fragments in living-related liver transplantation for inborn errors of metabolism. Data Brief. 29 , 105183 (2020). Wang, J. W. et al. Cell-free fetal DNA testing and its correlation with prenatal indications. BMC Pregnancy Childbirth . 21 , 585 (2021). Sherwood, K. & Weimer, E. T. Characteristics, properties, and potential applications of circulating cell-free DNA in clinical diagnostics: a focus on transplantation. J. Immunol. Methods . 463 , 27–38 (2018). Gielis, E. M. et al. Plasma donor-derived cell-free DNA kinetics after kidney transplantation using a single tube multiplex PCR assay. PLoS One . 13 , e0208207 (2018). Snyder, T. M., Khush, K. K., Valantine, H. A. & Quake, S. R. Universal noninvasive detection of solid organ transplant rejection. Proc. Natl. Acad. Sci. U.S.A. 108, 6229–6234 (2011). Zhao, D. et al. Preliminary clinical experience applying donor-derived cell-free DNA to discern rejection in pediatric liver transplant recipients. Sci. Rep. 11 , 1138 (2021). Jordan, S. C. et al. Donor-derived cell-free DNA identifies antibody-mediated rejection in donor specific antibody positive kidney transplant recipients. Transpl. Direct . 4 , e379 (2018). Schutz, E. et al. Graft-derived cell-free DNA, a noninvasive early rejection and graft damage marker in liver transplantation: a prospective, observational, multicenter cohort study. PLoS Med. 14 , e1002286 (2017). Kanamori, H. et al. Noninvasive graft monitoring using donor-derived cell-free DNA in Japanese liver transplantation. Hepatol. Res. 54 , 300–314 (2024). Fernandez-Galan, E. et al. Monitoring of donor-derived cell-free DNA by short tandem repeats: concentration of total cell-free DNA and fragment size for acute rejection risk assessment in liver transplantation. Liver Transpl. 28 , 257–268 (2022). Chinnappan, R. et al. Low-cost point-of-care monitoring of ALT and AST is promising for faster decision making and diagnosis of acute liver injury. Diagnostics (Basel . 13 , 18 (2023). Beck, J. et al. Digital droplet PCR for rapid quantification of donor DNA in the circulation of transplant recipients as a potential universal biomarker of graft injury. Clin. Chem. 59 , 1732–1741 (2013). Gadi, V. K. et al. Soluble donor DNA concentrations in recipient serum correlate with pancreas-kidney rejection. Clin. Chem. 52 , 379–382 (2006). American Society of Transplant Surgeons. ASTS Statement on donor-derived cell-free DNA (dd-cfDNA) – Updated. (pdf).Oct. (2024). Tables Table 1. Clinical characteristics of the liver transplant recipient cohort, stratified by underlying disease etiology. Group Etiology Age (years) Sex Distribution Number of Patients Alcohol Alcoholic liver disease 31–70 3 women, 10 men 13 Autoimmune AIH, PSC, PBC 20–63 10 women, 10 men 20 Viral HCV, HBV 31–74 5 women, 4 men 9 Cancer HCC, cholangiocarcinoma 29–70 3 women, 7 men 10 Others ALF, PLD, HEHE, NAFLD, trauma, etc. 23–67 11 women, 7 men 18 Abbreviations: AIH – autoimmune hepatitis; PSC – primary sclerosing cholangitis; PBC – primary biliary cholangitis; HCC – hepatocellular carcinoma; ALF – acute liver failure; PLD – polycystic liver disease; HEHE – hepatic epithelioid hemangioendothelioma; NAFLD – non-alcoholic fatty liver disease. Table 2. Correlation between total cfDNA levels and laboratory parameters using Kendall’s Tau test. Variable Kendall’s Tau p-value ALT -0.085 0.390 AST -0.059 0.547 ALP -0.049 0.616 Tacrolimus 0.063 0.519 Note: No statistically significant correlations were found between cfDNA concentration and any laboratory parameter. Table 3. Comparison of cfDNA levels across liver disease etiology groups using Kruskal-Wallis test. Test p-value Kruskal-Wallis test 0.290 Conclusion: No statistically significant differences were observed in cfDNA levels between the different etiologic groups of liver disease. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7077786","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":492634261,"identity":"d5705bb0-6c19-45d5-8fac-4a8df24dfbfb","order_by":0,"name":"Monika Kolanowska","email":"","orcid":"","institution":"Wiedziec Wiecej Foundation","correspondingAuthor":false,"prefix":"","firstName":"Monika","middleName":"","lastName":"Kolanowska","suffix":""},{"id":492634262,"identity":"ad4c1e2a-326f-4f6c-93dd-b73049dd11fd","order_by":1,"name":"Jakub Franke","email":"","orcid":"","institution":"Medical University of Warsaw","correspondingAuthor":false,"prefix":"","firstName":"Jakub","middleName":"","lastName":"Franke","suffix":""},{"id":492634263,"identity":"d3497ec2-251a-409c-b542-a44c97b1388e","order_by":2,"name":"Anna Wójcicka","email":"","orcid":"","institution":"Wiedziec Wiecej Foundation","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Wójcicka","suffix":""},{"id":492634264,"identity":"7a297b3f-f1d8-4b67-b9e4-5a6886b59b31","order_by":3,"name":"Karolina Wronka","email":"","orcid":"","institution":"Medical University of Warsaw","correspondingAuthor":false,"prefix":"","firstName":"Karolina","middleName":"","lastName":"Wronka","suffix":""},{"id":492634266,"identity":"579af6f5-146e-420a-a333-c8362deee4bf","order_by":4,"name":"Maciej Wójcicki","email":"","orcid":"","institution":"Medical University of Warsaw","correspondingAuthor":false,"prefix":"","firstName":"Maciej","middleName":"","lastName":"Wójcicki","suffix":""},{"id":492634267,"identity":"f0f3d28e-ba9c-4402-a3c5-e7a640badd5d","order_by":5,"name":"Oskar Kornasiewicz","email":"","orcid":"","institution":"Medical University of Warsaw","correspondingAuthor":false,"prefix":"","firstName":"Oskar","middleName":"","lastName":"Kornasiewicz","suffix":""},{"id":492634269,"identity":"f6672be4-a5c3-451e-9142-8df03787f13f","order_by":6,"name":"Marek Krawczyk","email":"","orcid":"","institution":"Medical University of Warsaw","correspondingAuthor":false,"prefix":"","firstName":"Marek","middleName":"","lastName":"Krawczyk","suffix":""},{"id":492634270,"identity":"bbd62843-e0e9-48ed-bf0d-f79bfc3cb61b","order_by":7,"name":"Joanna Raszeja-Wyszomirska","email":"data:image/png;base64,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","orcid":"","institution":"Medical University of Warsaw","correspondingAuthor":true,"prefix":"","firstName":"Joanna","middleName":"","lastName":"Raszeja-Wyszomirska","suffix":""}],"badges":[],"createdAt":"2025-07-08 19:53:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7077786/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7077786/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88759041,"identity":"2a7f50bc-2dd3-4c1c-b7ae-9f7c2277d5a7","added_by":"auto","created_at":"2025-08-11 07:39:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":551189,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7077786/v1/5956b880-3b4c-4ff5-a4f7-1214ad4a1972.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of Total Circulating Cell-Free DNA as a Biomarker in Liver Transplant Recipients: A Single-Center Pilot Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLiver transplantation (LT) remains the definitive treatment for end-stage liver disease. In 2024, over 600 liver transplants were performed in Poland alone [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Despite advancements, post-transplant monitoring largely relies on liver function tests (LFTs), including ALT, AST, bilirubin, gamma-glutamyl transferase, and ALP [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, these markers are neither highly specific nor immediate indicators of graft injury. Liver biopsy remains the gold standard for rejection diagnosis, but its invasiveness and delayed turnaround necessitate alternative biomarkers [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCirculating cell-free DNA (cfDNA), first described in 1948 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], has since gained relevance in oncology [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], prenatal medicine [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and transplantology [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Donor-derived cfDNA (dd-cfDNA) has been especially promising in detecting subclinical rejection [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Its short half-life (16 minutes to 2.5 hours) enables real-time monitoring [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, dd-cfDNA assays require genotyping and are cost-prohibitive for routine use.\u003c/p\u003e\u003cp\u003eThis study explored whether total cfDNA, regardless of origin, could serve as an accessible biomarker to complement standard LFTs in early detection of graft dysfunction.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthical Approval\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e The study was approved by the Bioethics Committee of the Medical University of Warsaw (KB/186/2021). Written informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy Group\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Seventy LT recipients (aged 20\u0026ndash;74) were stratified by underlying liver disease: alcohol-induced (n=13), autoimmune (n=20), viral (HBV/HCV, n=9), cancer (HCC/cholangiocarcinoma, n=10), and others (n=18). Detailed group demographics are provided in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSample Collection and Processing\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Peripheral blood (5 ml) was collected into K3 EDTA tubes 10 days post-LT and processed at 4\u0026deg;C. Plasma was separated via dual centrifugation and stored at -80\u0026deg;C. cfDNA was extracted using the Cobas\u0026reg; cfDNA Sample Preparation Kit (Roche) and analyzed using the Quantus fluorometer (Promega). Fragment size was verified using the Agilent TapeStation system.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Analysis\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Non-parametric statistical methods were employed. Kendall\u0026rsquo;s Tau was used to assess correlations between cfDNA and ALT, AST, ALP, and tacrolimus trough levels. The Kruskal-Wallis test evaluated cfDNA differences across liver disease groups. Significance was set at p\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003eAll methods were performed in accordance with the relevant guidelines and regulations\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTotal cfDNA was successfully extracted from all 70 patients. Median concentration was 11 ng/ml. Three patients (autoimmune and cancer groups) had peak levels of 70 ng/ml. Five patients exhibited cfDNA levels \u0026lt;3 ng/ml, notably excluding the cancer group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo significant associations were found between cfDNA levels and standard clinical parameters. Specifically, Kendall\u0026rsquo;s Tau correlation analysis did not demonstrate any statistically significant relationships between cfDNA concentration and commonly used blood biomarkers, including alanine aminotransferase (ALT) (Tau = -0.085, \u003cem\u003ep\u003c/em\u003e = 0.390), aspartate aminotransferase (AST) (Tau = -0.0594, \u003cem\u003ep\u003c/em\u003e = 0.547), and alkaline phosphatase (ALP) (Tau = -0.049, \u003cem\u003ep\u003c/em\u003e = 0.616). Similarly, no significant correlation was found between cfDNA levels and tacrolimus dosage (Tau = 0.063, \u003cem\u003ep\u003c/em\u003e = 0.519). These results are summarized in Table 2.\u003c/p\u003e\n\u003cp\u003eFurthermore, to explore whether cfDNA levels varied among different liver disease etiologies, a Kruskal\u0026ndash;Wallis test was conducted. This analysis also did not reveal any statistically significant differences across the etiological subgroups (\u003cem\u003ep\u003c/em\u003e = 0.29), as presented in Table 3.\u003c/p\u003e\n\u003cp\u003eIn a subgroup analysis of 21 patients with cfDNA \u0026ge;20 ng/ml, a moderate correlation was observed between cfDNA and ALT (Tau = 0.46, p = 0.0105), though clinical relevance remains unclear.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eRecent studies have demonstrated that cell-free DNA (cfDNA) is a sensitive and specific biomarker for early detection of various pathological processes [6, 13-15]. It has been successfully implemented in diagnostic applications across multiple disciplines, including oncology [11, 13], prenatal testing [16], and transplant medicine ([10, 12, 17-20]. Two main characteristics make cfDNA a particularly promising biomarker: its rapid increase in response to inflammatory stimuli and its tissue-specific origin, allowing for potential discrimination between donor- and recipient-derived fractions [21].\u003c/p\u003e\n\u003cp\u003eIn the context of solid organ transplantation, donor-derived cfDNA (dd-cfDNA) has been extensively studied as an early indicator of graft injury. It has been shown to increase in response to both acute rejection and infectious complications [10]. A prospective, multicenter study conducted in German transplant centers confirmed that dd-cfDNA monitoring enables earlier and more sensitive detection of acute rejection compared to standard liver function tests (LFTs) [22]. In another study, Japanese researchers monitored cfDNA and dd-cfDNA levels in 91 liver transplant recipients over a 30-day period. Using 300 single nucleotide polymorphisms (SNPs) for discrimination, they demonstrated high prognostic accuracy of dd-cfDNA for graft injury [23]. Similarly, a pediatric study reported an area under the curve (AUC) greater than 0.84 for cfDNA-based rejection detection, outperforming traditional biomarkers [16]. Moreover, a pilot trial involving 59 patients revealed that cfDNA levels rose before abnormalities in LFTs became evident, suggesting earlier detection of graft dysfunction [24].\u003c/p\u003e\n\u003cp\u003eBuilding on these findings, the present study aimed to evaluate whether total cfDNA, measured without fractionating donor-derived components, could serve as a rapid and accessible biomarker for liver graft injury. The test protocol was designed to deliver results within approximately three hours, making it potentially feasible for use in routine clinical laboratories. However, our findings did not show statistically significant correlations between total cfDNA levels and traditional liver biomarkers such as ALT, AST, and ALP. Likewise, no significant association was observed between cfDNA concentration and tacrolimus dosing, nor were cfDNA levels significantly different among patients with various liver disease etiologies (Tables 2\u0026ndash;3). These results highlight the complex biological nature of cfDNA dynamics. Unlike dd-cfDNA, which directly reflects graft cell turnover, total cfDNA includes DNA fragments originating from multiple tissues and may be influenced by systemic inflammation, surgical trauma, or other non-specific factors. The absence of statistically significant correlations may reflect this lack of specificity. Notably, in a subgroup of patients with the highest cfDNA concentrations, a moderate correlation with ALT was observed. Given that ALT is regarded as the most specific enzymatic indicator of hepatocellular damage [25], this observation could reflect subclinical graft injury not captured by standard LFTs. Elevated cfDNA concentrations have previously been associated with increased risk of acute rejection [26, 27], supporting the relevance of this signal, though longitudinal data and histological confirmation would be required for validation.\u003c/p\u003e\n\u003cp\u003eRecent literature further supports the superiority of dd-cfDNA over total cfDNA. dd-cfDNA has been shown to correlate well with biopsy-confirmed rejection and typically increases earlier than conventional biomarkers [17, 20]. Moreover, novel approaches are under development. For example, quantification of mitochondrial cfDNA (mt-cfDNA) during ex vivo machine perfusion has demonstrated correlation with post-transplant liver function, offering a promising tool for organ viability assessment [21]. Similarly, epigenetic analyses of cfDNA, particularly methylation-based profiling, may enhance specificity by distinguishing hepatocyte-derived fragments from those of cholangiocyte or non-hepatic origin [10]. Despite these advances, dd-cfDNA testing has not yet been widely implemented in routine clinical practice. As of 2024, the American Society of Transplant Surgeons (ASTS) does not recommend routine dd-cfDNA surveillance post-liver transplantation due to insufficient high-level evidence (ASTS Position Statement, 2024) [28]. Nevertheless, ongoing prospective trials and technological improvements are likely to facilitate broader clinical adoption in the future.\u003c/p\u003e\n\u003cp\u003eTotal cfDNA, while less specific, remains attractive for its simplicity, low cost, and fast turnaround time. It may have particular value in resource-limited settings or as an initial triage tool to identify patients requiring further evaluation using more complex dd-cfDNA-based assays. Future studies should consider incorporating cfDNA kinetics, fragmentation patterns, and epigenetic features to enhance diagnostic accuracy without requiring full genotyping.\u003c/p\u003e\n\u003cp\u003eLimitations of the current study include the small sample size, single time-point sampling, and lack of histological validation of graft injury. Inter-patient variability in cfDNA kinetics and clearance, as well as concurrent systemic inflammation, may also have influenced the results. Nonetheless, the feasibility of the method and the observed trends support further investigation.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eTotal cfDNA quantification is feasible and logistically simple, but does not demonstrate sufficient sensitivity or specificity to serve as a standalone marker for liver graft injury. Its role may lie in early screening or as part of a multi-analyte biomarker panel. Donor-derived cfDNA remains the more promising candidate for early detection of transplant rejection. Further large-scale, longitudinal studies are needed to validate cfDNA-based monitoring strategies and to refine their clinical applicability.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAll the authors (MK, JF, AW, KW, MW, OK, MK, JR-W) contributed to the experimental design, interpretation of the results, drafting of the manuscript and its final approval. MK performed experiments and JF contributed to data analysis. The main person responsible for the drafting of the manuscript was J R-W.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eData is provided within the manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCentrum Organizacyjno-. Koordynacyjne do Spraw Transplantacji. Statystyka 2024 \u0026ndash; POLTRANSPLANT. (pdf).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePerottino, G., Harrington, C. \u0026amp; Levitsky, J. Biomarkers of rejection in liver transplantation. \u003cem\u003eCurr. Opin. Organ. Transpl.\u003c/em\u003e \u003cb\u003e27\u003c/b\u003e, 154\u0026ndash;158 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRaszeja-Wyszomirska, J. et al. Free-circulating nucleic acids as biomarkers in patients after solid organ transplantation. \u003cem\u003eAnn. Transpl.\u003c/em\u003e \u003cb\u003e28\u003c/b\u003e, e939750 (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMandel, P. \u0026amp; Metais, P. Nuclear acids in human blood plasma. \u003cem\u003eC R Seances Soc. Biol. Fil\u003c/em\u003e. \u003cb\u003e142\u003c/b\u003e, 241\u0026ndash;243 (1948).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStawski, R. et al. Current trends in cell-free DNA applications. 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Elevated fractional donor-derived cell-free DNA during subclinical graft injury after liver transplantation. \u003cem\u003eLiver Transpl.\u003c/em\u003e \u003cb\u003e28\u003c/b\u003e, 1911\u0026ndash;1919 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKnight, S. R., Thorne, A. \u0026amp; Lo Faro, M. L. Donor-specific cell-free DNA as a biomarker in solid organ transplantation: a systematic review. \u003cem\u003eTransplantation\u003c/em\u003e103, 273\u0026ndash;283 (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBronkhorst, A. J., Ungerer, V. \u0026amp; Holdenrieder, S. The emerging role of cell-free DNA as a molecular marker for cancer management. \u003cem\u003eBiomol. Detect. Quantif\u003c/em\u003e. \u003cb\u003e17\u003c/b\u003e, 100087 (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKataria, A., Kumar, D. \u0026amp; Gupta, G. Donor-derived cell-free DNA in solid-organ transplant diagnostics: indications, limitations, and future directions. \u003cem\u003eTransplantation\u003c/em\u003e105, 1203\u0026ndash;1211 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJamshidi, A. et al. Evaluation of cell-free DNA approaches for multi-cancer early detection. \u003cem\u003eCancer Cell.\u003c/em\u003e \u003cb\u003e40\u003c/b\u003e, 1537\u0026ndash;1549e12 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhou, M. et al. Circulating organ-specific microRNAs serve as biomarkers in organ-specific diseases: implications for organ allo- and xeno-transplantation. \u003cem\u003eInt. J. Mol. Sci.\u003c/em\u003e \u003cb\u003e17\u003c/b\u003e, 8 (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhu, X. et al. Sequencing data of cell-free DNA fragments in living-related liver transplantation for inborn errors of metabolism. \u003cem\u003eData Brief.\u003c/em\u003e \u003cb\u003e29\u003c/b\u003e, 105183 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang, J. W. et al. Cell-free fetal DNA testing and its correlation with prenatal indications. \u003cem\u003eBMC Pregnancy Childbirth\u003c/em\u003e. \u003cb\u003e21\u003c/b\u003e, 585 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSherwood, K. \u0026amp; Weimer, E. T. Characteristics, properties, and potential applications of circulating cell-free DNA in clinical diagnostics: a focus on transplantation. \u003cem\u003eJ. Immunol. Methods\u003c/em\u003e. \u003cb\u003e463\u003c/b\u003e, 27\u0026ndash;38 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGielis, E. M. et al. Plasma donor-derived cell-free DNA kinetics after kidney transplantation using a single tube multiplex PCR assay. \u003cem\u003ePLoS One\u003c/em\u003e. \u003cb\u003e13\u003c/b\u003e, e0208207 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSnyder, T. M., Khush, K. K., Valantine, H. A. \u0026amp; Quake, S. R. Universal noninvasive detection of solid organ transplant rejection. \u003cem\u003eProc. Natl. Acad. Sci. U.S.A.\u003c/em\u003e108, 6229\u0026ndash;6234 (2011).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao, D. et al. Preliminary clinical experience applying donor-derived cell-free DNA to discern rejection in pediatric liver transplant recipients. \u003cem\u003eSci. Rep.\u003c/em\u003e \u003cb\u003e11\u003c/b\u003e, 1138 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJordan, S. C. et al. Donor-derived cell-free DNA identifies antibody-mediated rejection in donor specific antibody positive kidney transplant recipients. \u003cem\u003eTranspl. Direct\u003c/em\u003e. \u003cb\u003e4\u003c/b\u003e, e379 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchutz, E. et al. Graft-derived cell-free DNA, a noninvasive early rejection and graft damage marker in liver transplantation: a prospective, observational, multicenter cohort study. \u003cem\u003ePLoS Med.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e, e1002286 (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKanamori, H. et al. Noninvasive graft monitoring using donor-derived cell-free DNA in Japanese liver transplantation. \u003cem\u003eHepatol. Res.\u003c/em\u003e \u003cb\u003e54\u003c/b\u003e, 300\u0026ndash;314 (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFernandez-Galan, E. et al. Monitoring of donor-derived cell-free DNA by short tandem repeats: concentration of total cell-free DNA and fragment size for acute rejection risk assessment in liver transplantation. \u003cem\u003eLiver Transpl.\u003c/em\u003e \u003cb\u003e28\u003c/b\u003e, 257\u0026ndash;268 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChinnappan, R. et al. Low-cost point-of-care monitoring of ALT and AST is promising for faster decision making and diagnosis of acute liver injury. \u003cem\u003eDiagnostics (Basel\u003c/em\u003e. \u003cb\u003e13\u003c/b\u003e, 18 (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBeck, J. et al. Digital droplet PCR for rapid quantification of donor DNA in the circulation of transplant recipients as a potential universal biomarker of graft injury. \u003cem\u003eClin. Chem.\u003c/em\u003e \u003cb\u003e59\u003c/b\u003e, 1732\u0026ndash;1741 (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGadi, V. K. et al. Soluble donor DNA concentrations in recipient serum correlate with pancreas-kidney rejection. \u003cem\u003eClin. Chem.\u003c/em\u003e \u003cb\u003e52\u003c/b\u003e, 379\u0026ndash;382 (2006).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAmerican Society of Transplant Surgeons. ASTS Statement on donor-derived cell-free DNA (dd-cfDNA) \u0026ndash; Updated. (pdf).Oct. (2024).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003ch2\u003eTable 1. Clinical characteristics of the liver transplant recipient cohort, stratified by underlying disease etiology.\u003c/h2\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eEtiology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eSex Distribution\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eNumber of Patients\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eAlcohol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eAlcoholic liver disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e31\u0026ndash;70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e3 women, 10 men\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eAutoimmune\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eAIH, PSC, PBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e20\u0026ndash;63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e10 women, 10 men\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eViral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eHCV, HBV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e31\u0026ndash;74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e5 women, 4 men\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eCancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eHCC, cholangiocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e29\u0026ndash;70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e3 women, 7 men\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eALF, PLD, HEHE, NAFLD, trauma, etc.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e23\u0026ndash;67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e11 women, 7 men\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: AIH \u0026ndash; autoimmune hepatitis; PSC \u0026ndash; primary sclerosing cholangitis; PBC \u0026ndash; primary biliary cholangitis; HCC \u0026ndash; hepatocellular carcinoma; ALF \u0026ndash; acute liver failure; PLD \u0026ndash; polycystic liver disease; HEHE \u0026ndash; hepatic epithelioid hemangioendothelioma; NAFLD \u0026ndash; non-alcoholic fatty liver disease.\u003c/p\u003e\n\u003ch2\u003e\u0026nbsp;\u003c/h2\u003e\n\u003ch2\u003eTable 2. Correlation between total cfDNA levels and laboratory parameters using Kendall\u0026rsquo;s Tau test.\u003c/h2\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eKendall\u0026rsquo;s Tau\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eALT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e-0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e0.390\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eAST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e-0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e0.547\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eALP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e-0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e0.616\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eTacrolimus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e0.519\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: No statistically significant correlations were found between cfDNA concentration and any laboratory parameter.\u003c/p\u003e\n\u003ch2\u003e\u0026nbsp;\u003c/h2\u003e\n\u003ch2\u003eTable 3. Comparison of cfDNA levels across liver disease etiology groups using Kruskal-Wallis test.\u003c/h2\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50%;\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50%;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50%;\"\u003e\n \u003cp\u003eKruskal-Wallis test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50%;\"\u003e\n \u003cp\u003e0.290\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eConclusion: No statistically significant differences were observed in cfDNA levels between the different etiologic groups of liver disease.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"liver transplantation, cell-free DNA, biomarker, graft rejection, dd-cfDNA","lastPublishedDoi":"10.21203/rs.3.rs-7077786/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7077786/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDonor-derived cell-free DNA (dd-cfDNA) has shown promise as a sensitive non-invasive biomarker of graft injury following liver transplantation (LT). This pilot study assessed whether total cfDNA levels alone could reflect liver graft health and predict rejection events. To analyze this, 70 adult LT recipients were stratified by underlying liver disease etiology and monitored for 18 months. Total cfDNA was extracted from plasma samples collected 10 days post-LT and quantified fluorometrically. Associations between cfDNA levels and standard liver function biomarkers (ALT, AST, ALP or tacrolimus dosing) were analyzed using Kendall\u0026rsquo;s Tau. Differences in cfDNA levels among disease etiologies were assessed using the Kruskal-Wallis test. Median cfDNA concentration was 11 ng/ml (range: \u0026lt;3\u0026ndash;70 ng/ml). Highest concentrations were noted in patients with autoimmune liver disease or hepatocellular carcinoma. No significant correlation was observed between cfDNA and ALT, AST, ALP, or tacrolimus levels. A subset of patients with cfDNA\u0026thinsp;\u0026ge;\u0026thinsp;20 ng/ml (n\u0026thinsp;=\u0026thinsp;21) showed a moderate correlation with ALT (Tau\u0026thinsp;=\u0026thinsp;0.46, p\u0026thinsp;=\u0026thinsp;0.0105). cfDNA levels did not differ between etiological groups. These findings suggest that while total cfDNA reflects some inflammatory activity, it lacks the specificity of dd-cfDNA in clinical transplant monitoring. Larger studies and fraction-specific analysis are warranted.\u003c/p\u003e","manuscriptTitle":"Evaluation of Total Circulating Cell-Free DNA as a Biomarker in Liver Transplant Recipients: A Single-Center Pilot Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-30 08:48:17","doi":"10.21203/rs.3.rs-7077786/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d976d194-26b5-43e5-a980-3524169ef655","owner":[],"postedDate":"July 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":52309580,"name":"Health sciences/Biomarkers"},{"id":52309581,"name":"Health sciences/Diseases"},{"id":52309582,"name":"Health sciences/Gastroenterology"},{"id":52309583,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2025-08-11T07:38:20+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-30 08:48:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7077786","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7077786","identity":"rs-7077786","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}