Comparison of methods for donor-derived cell-free DNA quantification in plasma and urine from solid organ transplant recipients

Clinical Examples of the Additive Value of Absolute Quantification of Cell-Free DNA After Heart Transplantation

OBJECTIVE

Cell-free DNA (cfDNA) is used as a biomarker after transplantation to detect graft injury, relying on the donor fraction (DF). We have established a PCR-based approach allowing us to separately quantify absolute values of dd-cfDNA and recipient-derived cfDNA (rd-cfDNA). We aimed to present typical clinical scenarios after heart transplantation (HTx) to illustrate the advantages of absolute cfDNA values over DF.

METHODS

We used the cfDNA results of our cohort (509 samples of 52 patients followed during the first year after HTx) as background and determined the trajectories of cfDNA in specific clinical situations. We profiled an uncomplicated clinical course, viral and bacterial infections, acute and chronic rejection, and false-negative and false-positive rejections in six patients (five adults, one child).

RESULTS

There was a substantial discrepancy between relative (DF) and absolute cfDNA-levels in several clinical situations. Rd- and dd-cfDNA were independently elevated during episodes of rejection and infection and were better suited to depict treatment response than DF alone.

CONCLUSIONS

Absolute quantification of cfDNA may offer clinically relevant information additive to DF in various situations after HTx and could be helpful for more accurate monitoring of diagnosis and treatment of rejection.

Multi-centre analytical performance verification of an IVD assay to quantify donor-derived cell-free DNA in solid organ transplant recipients

Donor-derived cell-free DNA (dd-cfDNA) has been widely studied as biomarker for non-invasive allograft rejection monitoring. Earlier rejection detection enables more prompt diagnosis and intervention, ultimately improving patient treatment and outcomes. This multi-centre study aims to verify analytical performance of a next-generation sequencing-based dd-cfDNA assay at end-user environments. Three independent laboratories received the same experimental design and 16 blinded samples to perform cfDNA extraction and the dd-cfDNA assay workflow. dd-cfDNA results were compared between sites and against manufacturer validation to evaluate concordance, reproducibility, repeatability and verify analytical performance. A total of 247 sample libraries were generated across 18 runs, with completion time of <24 h. A 96.0% first pass rate highlighted minimal failures. Overall observed versus expected dd-cfDNA results demonstrated good concordance and a strong positive correlation with linear least squares regression r2 = 0.9989, and high repeatability and reproducibility within and between sites, respectively (p > 0.05). Manufacturer validation established limit of blank 0.18%, limit of detection 0.23% and limit of quantification 0.23%, and results from independent sites verified those limits. Parallel analyses illustrated no significant difference (p = 0.951) between dd-cfDNA results with or without recipient genotype. The dd-cfDNA assay evaluated here has been verified as a reliable method for efficient, reproducible dd-cfDNA quantification in plasma from solid organ transplant recipients without requiring genotyping. Implementation of onsite dd-cfDNA testing at clinical laboratories could facilitate earlier detection of allograft injury, bearing great potential for patient care.

Principles of digital sequencing using unique molecular identifiers

Massively parallel sequencing technologies have long been used in both basic research and clinical routine. The recent introduction of digital sequencing has made previously challenging applications possible by significantly improving sensitivity and specificity to now allow detection of rare sequence variants, even at single molecule level. Digital sequencing utilizes unique molecular identifiers (UMIs) to minimize sequencing-induced errors and quantification biases. Here, we discuss the principles of UMIs and how they are used in digital sequencing. We outline the properties of different UMI types and the consequences of various UMI approaches in relation to experimental protocols and bioinformatics. Finally, we describe how digital sequencing can be applied in specific research fields, focusing on cancer management where it can be used in screening of asymptomatic individuals, diagnosis, treatment prediction, prognostication, monitoring treatment efficacy and early detection of treatment resistance as well as relapse.

Non-invasive molecular biomarkers for monitoring solid organ transplantation: A comprehensive overview

Solid organ transplantation is a life-saving intervention for individuals with end-stage organ failure. Despite the effectiveness of immunosuppressive therapy, the risk of graft rejection persists in all viable transplants between individuals. The risk of rejection may vary depending on the degree of compatibility between the donor and recipient for both human leucocyte antigen (HLA) and non-HLA gene-encoded products. Monitoring the status of the allograft is a critical aspect of post-transplant management, with invasive biopsies being the standard of care for detecting rejection. Non-invasive biomarkers are increasingly being recognized as valuable tools for aiding in the detection of graft rejection, monitoring graft status and evaluating the efficacy of immunosuppressive therapy. Here, we focus on the importance of molecular biomarkers in solid organ transplantation and their potential role in clinical practice. Conventional molecular biomarkers used in transplantation include HLA typing, detection of anti-HLA antibodies, killer cell immunoglobulin-like receptor genotypes, and anti-MHC class 1-related chain A antibodies, which are important for assessing the compatibility of the donor and recipient. Emerging molecular biomarkers include the detection of donor-derived cell-free DNA, microRNAs (regulation of gene expression), exosomes (small vesicles secreted by cells), and kidney solid organ response test, in the recipient's blood for early signs of rejection. This review highlights the strengths and limitations of these molecular biomarkers and their potential role in improving transplant outcomes.

Detection of donor-derived cell-free DNA in the setting of multiple kidney transplantations

Background

The routine use of donor-derived cell-free DNA (dd-cfDNA) assays to monitor graft damage in patients after kidney transplantation is being implemented in many transplant centers worldwide. The interpretation of the results can be complicated in the setting of multiple sequential kidney transplantations where accurate donor assignment of the detected dd-cfDNA can be methodologically challenging.

Methods

We investigated the ability of a new next-generation sequencing (NGS)-based dd-cfDNA assay to accurately identify the source of the detected dd-cfDNA in artificially generated samples as well as clinical samples from 31 patients who had undergone two sequential kidney transplantations.

Results

The assay showed a high accuracy in quantifying and correctly assigning dd-cfDNA in our artificially generated chimeric sample experiments over a clinically meaningful quantitative range. In our clinical samples, we were able to detect dd-cfDNA from the first transplanted (nonfunctioning) graft in 20% of the analyzed patients. The amount of dd-cfDNA detected from the first graft was consistently in the range of 0.1%-0.6% and showed a fluctuation over time in patients where we analyzed sequential samples.

Conclusion

This is the first report on the use of a dd-cfDNA assay to detect dd-cfDNA from multiple kidney transplants. Our data show that a clinically relevant fraction of the transplanted patients have detectable dd-cfDNA from the first donor graft and that the amount of detected dd-cfDNA is in a range where it could influence clinical decision-making.

Assessment of Donor Derived Cell Free DNA (dd-cfDNA) at Surveillance and at Clinical Suspicion of Acute Rejection in Renal Transplantation

In our prospective, unicenter cohort study, we collected blood samples from 30 newly kidney transplanted patients, at month 1, 2, 3, and 5 for dd-cfDNA analysis, along with creatinine/eGFR and DSA monitoring, and from 32 patients who underwent an indication biopsy and whose dd-cfDNA levels were measured at the time of biopsy and 1 month afterwards. Fourteen of 32 (43.8%) patients in the biopsy group were diagnosed with TCMR and 5 of 32 (15.6%) with ABMR. Dd-cfDNA proved to be better than creatinine in diagnosing rejection from non-rejection in patients who were biopsied. When a dd-cfDNA threshold of 0.5% was chosen, sensitivity was 73.7% and specificity was 92.3% (AUC: 0.804, 0.646-0.961). In rejection patients, levels of dd-cfDNA prior to biopsy (0.94%, 0.3-2.0) decreased substantially after initiation of treatment with median returning to baseline already at 1 month (0.33%, 0.21-0.51, p = 0.0036). In the surveillance group, high levels of dd-cfDNA (>0.5%) from second month post-transplantation were correlated with non-increasing eGFR 1 year post-transplantation. The study used AlloSeq kit for kidney transplant surveillance for first time and confirmed dd-cfDNA's ability to detect rejection and monitor treatment, as well as to predict worse long-term outcomes regarding eGFR.

Free-Circulating Nucleic Acids as Biomarkers in Patients After Solid Organ Transplantation

A number types of extracellular DNA (eg, cell-free, cfDNA) circulate in human blood, including mitochondrial, transcriptome, and regulatory DNA, usually at low concentrations. Larger amounts of cfDNA appear in any inflammatory condition, including organ damage due to a variety of reasons. The role of cfDNA in solid organ transplantation is discussed in this review as a valuable additional tool in the standard of care of transplant patients. Post-transplant monitoring requires the use of high-quality biomarkers for early detection of graft damage or rejection to be able to apply early therapeutic intervention. CfDNA complements the traditional monitoring strategies, being a risk stratification tool and an important prognostic marker. However, improving the sensitivity and specificity of cfDNA detection is necessary to facilitate personalized patient management, warranting further research in terms of measurement, test standardization, and storage, processing, and shipping. A diagnostic test (Allosure, CareDx, Inc., Brisbane, CA) for kidney, heart and lung transplant patients is now commercially available, and validation for other organs (eg, liver) is pending. To date, donor-derived cfDNA in combination with other biomarkers appears to be a promising tool in graft rejection as it is minimally invasive, time-sensitive, and cost-effective. However, improvement of sensitivity and specificity is required to facilitate personalized patient management. Whether it could be an alternate to graft biopsy remains unclear.

Investigation of Different Library Preparation and Tissue of Origin Deconvolution Methods for Urine and Plasma cfDNA Methylome Analysis

Methylation sequencing is a promising approach to infer the tissue of origin of cell-free DNA (cfDNA). In this study, a single- and a double-stranded library preparation approach were evaluated with respect to their technical biases when applied on cfDNA from plasma and urine. Additionally, tissue of origin (TOO) proportions were evaluated using two deconvolution methods. Sequencing cfDNA from urine using the double-stranded method resulted in a substantial within-read methylation bias and a lower global methylation (56.0% vs. 75.8%, p ≤ 0.0001) compared to plasma cfDNA, both of which were not observed with the single-stranded approach. Individual CpG site-based TOO deconvolution resulted in a significantly increased proportion of undetermined TOO with the double-stranded method (urine: 32.3% vs. 1.9%; plasma: 5.9% vs. 0.04%; p ≤ 0.0001), but no major differences in proportions of individual cell types. In contrast, fragment-level deconvolution led to multiple cell types, with significantly different TOO proportions between the two methods. This study thus outlines potential limitations of double-stranded library preparation for methylation analysis of cfDNA especially for urinary cfDNA. While the double-stranded method allows jagged end analysis in addition to TOO analysis, it leads to significant methylation bias in urinary cfDNA, which single-stranded methods can overcome.