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Updated: Mar 24, 2026

Detection of Residual Donor Erythroid Progenitor Cells after Hematopoietic Stem Cell Transplantation for Patients with Hemoglobinopathies
Published on: September 6, 2017
Advances in donor-derived cell-free DNA monitoring for solid organ transplantation
Darius Sairafi1, Emelie Foord1,2, Linnéa Pettersson1,2
1Devyser AB, Stockholm, Sweden.
Abstract:
Donor-derived cell-free DNA (dd-cfDNA) has emerged as a minimally invasive biomarker of allograft injury following solid organ transplantation. However, its clinical performance and interpretability depend strongly on how dd-cfDNA is measured, reported, and integrated into existing care pathways. This narrative review outlines the biological rationale for dd-cfDNA monitoring and explores the key preanalytical and analytical factors affecting test performance, with an emphasis on comparing measurement technologies and commonly used diagnostic systems. We examine major assay strategies, including next-generation sequencing approaches and PCR-based methods, including digital PCR, and discuss how assay design influences the need for donor/recipient genotyping, analytical sensitivity, susceptibility to clinical confounders (e.g., early post-operative injury, infection, leukopenia, and multi-organ DNA sources), turnaround time, batching, and quality control requirements in centralized versus decentralized testing models. We synthesize evidence for clinical validity and utility across transplanted organs, focusing on use cases such as early detection of injury, risk stratification, and supporting biopsy decisions, while highlighting ongoing challenges like threshold harmonization, inter-platform comparability, and imperfect specificity for distinguishing rejection from non-rejection injury. Overall, dd-cfDNA serves as a valuable adjunct for graft surveillance, but broader clinical applications will require standardized guidance for assay performance and reporting, platform-aware interpretation frameworks, and prospective outcome-focused studies to define optimal testing intervals and decision thresholds.
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