Microchimerism Matters: Advancing HSCT Monitoring Through NGS

Overview

Allogeneic haematopoietic stem cell transplantation (HSCT) remains the only curative therapeutic option for many haematological malignancies, including acute myeloid leukaemia (AML), acute lymphoblastic leukaemia (ALL), and myelodysplastic syndromes (MDS). Post-transplant monitoring is crucial to ensure durable engraftment, identify early risk of relapse, and guide pre-emptive interventions such as donor lymphocyte infusion (DLI), modifying immunosuppression, or targeted therapy. Historically, chimerism monitoring has relied heavily on short tandem repeat (STR) analysis; a method which provides robust quantification at moderate-to-high levels of donor/recipient cell fractions but suffers from limited sensitivity at the low end of the dynamic range.

In recent years, technological advancements such as quantitative PCR (qPCR), digital PCR (dPCR), and next-generation sequencing (NGS) have substantially enhanced the analytical sensitivity and precision of chimerism quantification. These sensitive methods can detect recipient DNA at levels as low as 0.01 to 0.1%, a full log lower than STR’s practical limit of detection (LoD) at 1 to 5%. The ability to detect low-level mixed chimerism (commonly termed microchimerism) with high reproducibility has led to a paradigm shift in how relapse risk is considered. Instead of waiting for ≥1 to 5% recipient DNA, often a late indicator of overt relapse, actionable biological changes can be identified weeks earlier.

The clinical relevance of this improved sensitivity is clear. Multiple studies, including both early VNTR-PCR work and more recent ultrasensitive qPCR/NGS assays, have shown that incremental increases in recipient-derived chimerism often precede morphological relapse in AML by a lead time of days to weeks (or even months in some cohorts). ¹ ² ³ When combined with lineage-specific chimerism testing (e.g. CD33⁺ myeloid cells or CD3⁺ T cells), microchimerism offers even greater predictive power. Lineage-restricted relapse may be observed in a cell subset long before it becomes apparent in whole blood or bone marrow, opening a larger therapeutic window for pre-emptive interventions.

In data presented at the American Society of Histocompatibility and Immunogenetics (ASHI) 51^st Annual Meeting in 2025, Dr Sanfilippo from the ASHI Engraftment Monitoring (EMO) Proficiency Scheme further strengthened the case for technological transition. Retrospectively reviewing proficiency results between 2018 and 2024, data from all participating labs showed that NGS exhibited substantially less inter-laboratory variability and fewer discrepant results than STR across the entire chimeric spectrum (0.1 to 100%). Dr Sanfilippo concluded with a statement that NGS may be better suited to detecting incremental chimerism changes and more accurately assessing relapse risk or treatment response. This represents one of the strongest profession-level signals to date that the field is moving towards more sensitive analytical solutions. ^⁴

Collectively, the available literature supports a clear conclusion; microchimerism is clinically meaningful, analytically achievable, and operationally necessary for modern post-HSCT surveillance. A shift towards NGS (through rationalising testing using existing molecular instrumentation) represents a logical evolution in transplant diagnostics to offer a more sensitive, reproducible, and clinically informative approach to patient care.

 

Introduction

Post-transplant chimerism describes the relative proportion of donor and recipient cells present in a patient’s blood or bone marrow following allogeneic HSCT. In the UK and Ireland, this testing is typically performed either within Histocompatibility and Immunogenetics (H&I) or at specialist Molecular Haematology/Molecular Genetics laboratories. Reports usually express chimerism as a percentage of donor DNA (e.g. 99% donor, 1% recipient) or vice versa.

Chimerism status informs:

• Engraftment success (e.g. early full donor chimerism often predicts good graft function).
• Graft rejection or failure (increasing recipient fractions indicate graft compromise).
• Early relapse detection (rising recipient DNA in the relevant lineage indicates resurgence of malignant clones).
• Immune reconstitution (e.g. T-cell chimerism correlates with graft-versus-host disease (GVHD) risk and immune recovery).

Chimerism monitoring therefore acts as a window into the dynamic biological processes occurring post-HSCT.

Traditional STR methods only reliably detect changes when recipient DNA exceeds ~1 to 5%. While this suffices for detecting late relapse or gross graft failure, it is inadequate for identifying early disease resurgence. The lowest recorded LOD for STR-based chimerism methods is at 1%, but many clonal expansions begin below this level, particularly in AML, where early relapse is often seeded by a small subset of malignant progenitors or blasts. ⁵ ⁶ ⁷ ⁸ By the time STR detects such a rise, the patient may already be symptomatic with the disease at clinically significant levels, leaving limited time for effective intervention.

Microchimerism-sensitive methods overcome this sensitivity gap by quantifying recipient DNA at levels far below 1%. Their ability to detect incremental changes is crucial because increasing mixed chimerism (IMC), even below 1%, can often be biologically meaningful and predictive of relapse. However, while whole blood chimerism provides a global snapshot, relapse frequently begins in specific haematopoietic compartments. For example:

• Myeloid lineage (CD33⁺) in AML.
• B-cell lineage (CD19⁺) in ALL.
• T-cell lineage (CD3⁺) in cases with immunological complications.

Cell separation techniques can be used to isolate these cells of interest, enabling lineage-restricted relapse to be detected earlier than whole blood analysis alone. This enhances the positive predictive value of chimerism monitoring and reduces risk when whole blood donor chimerism remains high, but disease persists in a specific fraction.

Chimerism Monitoring Technologies

Modern chimerism monitoring relies on a spectrum of analytical technologies which differ markedly in sensitivity, precision, scalability, and their ability to capture clinically meaningful changes in chimerism status.

STR (Short Tandem Repeat) analysis uses highly polymorphic microsatellite markers to distinguish donor from recipient genotypes. This remains one of the most commonly used approaches for chimerism testing. Its long clinical history means that the method is familiar to most clinicians and transplant teams, and the interpretation framework is well established. In the quantitative range above approximately 5% recipient DNA, STR-based assays generally perform reliably, offering reproducible and clinically meaningful estimates of donor–recipient contributions. However, several technical limitations constrain the usefulness of STR testing at lower levels of mixed chimerism. Stutter artefacts, inherent to PCR amplification of repeat regions, and allele dropout can both compromise the accurate quantification of minor recipient populations, particularly as measurements approach the lower end of the dynamic range. As a result, the practical limit of detection for recipient DNA in most STR workflows typically lies around 1 to 5%, even though theoretical analytical sensitivity may be slightly better under ideal conditions. Additional challenges arise from inter-laboratory variability, which can be substantial due to differences in STR marker sets, capillary electrophoresis platforms, analysis software and interpretation. This variability can complicate longitudinal comparison when testing is not performed within a single laboratory. Furthermore, because STRs lack the sensitivity required to reliably detect very low-frequency populations, they may be less suitable for lineage-specific or cell subset monitoring.

Quantitative PCR-based (qPCR) chimerism uses either insertion/deletion (InDel) or SNP (single-nucleotide polymorphism) markers. qPCR–based chimerism monitoring offers a clear improvement in analytical sensitivity compared with conventional STR analysis, with typical detection thresholds in the range of 0.1 to 1%. This enhanced sensitivity allows earlier identification of IMC populations, making qPCR a valuable tool for centres aiming to detect relapse or graft instability at an earlier stage. In addition, qPCR assays are relatively rapid, enabling fast turnaround times that support timely clinical decision-making, particularly when results may influence urgent interventions such as donor lymphocyte infusion or immunosuppression adjustment.

However, while qPCR-based chimerism testing represents an improvement over STR in sensitivity and turnaround time, it has several important constraints that restrict its suitability for routine clinical use. The biggest limitation is the methodological requirement for a donor-recipient reference set for each transplant pair. The qPCR workflow requires access to both genomes during each assay setup and calibration, meaning finite and irreplaceable donor or recipient DNA must be consumed. This is particularly problematic in settings where donor material is extremely limited or where multiple donors contribute to a single patient, such as double-cord transplants. Over time, the depletion of reference DNA becomes a non-trivial constraint that can undermine assay reliability and restrict future testing flexibility. Additionally, most assays rely on a limited number of informative, bi-allelic loci, and not all donor–recipient pairs have a sufficiently discriminatory marker set. The quantitative nature of qPCR also makes results susceptible to calibration bias, including variations in standard curve generation, reference materials, and instrument performance, all of which can affect accuracy if not tightly controlled. Finally, although qPCR is more sensitive than STR, the method struggles to reliably quantify microchimerism below 0.2% or accurately report chimerism when above 20 to 30%; at the very low level, assay noise, stochastic effects, and allele imbalance can compromise reproducibility, while the inaccuracy at the higher range becomes more pronounced as the minor fraction increases, reducing confidence in results that are critical for early detection of relapse or graft failure. For applications requiring sustained accuracy across the entire dynamic chimerism range, alternative approaches are generally considered more appropriate.

Digital PCR (dPCR), including digital droplet PCR (ddPCR), partitions reactions into thousands of droplets, allowing absolute quantification of target alleles. With typical sensitivities in the range of 0.01 to 0.1%, dPCR markedly outperforms both STR and qPCR methods, allowing confident quantification of microchimerism that would otherwise fall below the reliable detection limits of other platforms. This high level of analytical confidence is especially valuable in scenarios where early increases in recipient DNA may influence clinical management.

Despite these strengths, dPCR is not without limitations. Compared with NGS, its multiplexing capacity is modest, typically allowing only one or a small number of loci to be assessed per reaction. This means that extensive marker panels cannot be interrogated simultaneously, making it less suitable for comprehensive genomic coverage or lineage-specific monitoring that requires broader marker sets. Each dPCR assay must also be designed, optimised, and validated individually for each informative marker, which can be labour-intensive and adds complexity to implementation. Additionally, dPCR often requires dedicated instrumentation such as droplet generators, droplet readers, or specialised digital PCR platforms that may not be present in a typical H&I or Molecular Genetics laboratory. The need to purchase and maintain this equipment poses a significant barrier to adoption, particularly for laboratories with limited capital budgets. Finally, although dPCR excels at high-precision quantification, its inherently narrow genomic breadth means it is not ideal as the sole platform for chimerism monitoring. On its own, it cannot provide the marker redundancy offered by NGS, so may not be as appropriate for use in multi-donor transplant scenarios. For this reason, dPCR could be used as a complementary technique rather than a standalone solution, leveraging its strengths for confirmation of critical low-level findings while relying on other methods for routine surveillance.

Next-Generation Sequencing (NGS) represents the most significant methodological advancement in donor-recipient quantification in the last decade. Its high depth of sequencing, digital readout, broad dynamic range, and excellent reproducibility make it uniquely suited for detecting microchimerism and resolving complex engraftment scenarios. Current NGS assays routinely achieve sensitivities in the range of 0.01 to 0.1%, enabling reliable detection of microchimerism at levels far below the limits of STR or qPCR. This high analytical sensitivity is complemented by the ability to interrogate dozens of informative loci across the genome, providing substantial marker redundancy and reducing the likelihood that variation in any single region will distort overall interpretation. The use of large, stable marker sets also contributes to excellent reproducibility across runs and laboratories. In addition, NGS platforms readily support lineage-specific chimerism testing, allowing sensitive assessment of T-cell, myeloid, NK-cell, or CD34+ progenitor fractions where subtle shifts may signal early relapse or graft instability.

However, the performance of an NGS assay depends heavily on the type of genomic marker used. While some assays rely on large panels of SNPs, others have chosen InDels instead to provide a distinct analytical advantage, particularly for low-level detection. InDels offer superior discrimination between donor and recipient DNA because they are inherently less susceptible to sequencing error than SNPs. Most NGS instruments occasionally introduce base substitution errors during sequencing-by-synthesis, which are indistinguishable from true SNP variants when they occur at low frequency. In contrast, InDels create length differences rather than simple base substitutions, meaning that sequencing artefacts are far less likely to produce false-positive or false-negative signals. This difference reduces noise, improves the robustness of low-level detection, and provides greater confidence in results within the microchimerism range (i.e., the range most relevant for early predictions of relapse or graft failure).

The One Lambda Devyser NGS Chimerism kit uses a carefully curated panel of InDels chosen because they are population-independent, meaning the assay can be applied equally well across diverse global populations while requiring fewer total markers to ensure clinically sufficient donor-recipient discrimination. The benefit is substantial; even in cases involving multiple donors, the likelihood of having enough informative markers remains high without the need for extensive marker screening. This characteristic distinguishes InDel-based NGS from qPCR/dPCR/SNP-based NGS methods where panels often require dozens or even hundreds of markers to achieve the same result, and a major differentiator against STR methods where achieving sufficient numbers of informative loci can be problematic in multi-donor (i.e., double cord unit transplant, re-transplant) or related donor transplants.

Finally, while NGS historically carried the perception of significant infrastructural and logistical barriers, this is now less relevant for many laboratories. Most Molecular and H&I laboratories already operate sequencing instruments for other diagnostic applications, meaning that chimerism analysis can often be rationalised onto existing platforms without additional capital investment. The main remaining requirement is the availability of suitable bioinformatics pipelines, although these, too, are increasingly standardised, commercially supported, or integrated into turnkey chimerism kits. Although NGS implementation does involve higher initial validation and workflow setup costs compared with STR or qPCR, the per-sample cost can become comparable when assays are run at scale or multiplexed with other sequencing-based workflows. As a result, for many centres, NGS represents a practical and future-proof approach that combines very high sensitivity with broad genomic coverage.

Comparative Literature Review

A large body of research demonstrates that increasing mixed chimerism (IMC), especially within the microchimerism range, serves as an early warning of relapse. Below is a table sorted in ascending order summarising key findings from 17 different sources, all relevant and referenced for completeness, which is followed by a summary of the key findings.

 

 

Table 1. Comparative literature review of microchimerism studies.

Early studies using STR-based methodology established the concept that IMC precedes relapse; rising recipient chimerism predicted relapse in both adult and paediatric cohorts, while serial increases in mixed chimerism correlated with impending relapse. ⁹ ¹⁴ These studies laid the conceptual foundation but were limited by STR’s sensitivity. Modern dPCR and NGS studies produced clearer, earlier signals:

• Valero-García et al. (2019) showed ddPCR detected relapse-associated chimerism days to weeks earlier than qPCR.¹²
• Haugaard et al. (2023) reported that NGS-based chimerism predicted relapse in paediatric patients with high accuracy, often weeks before routine methods.²⁰
• Liacini et al. (2023) demonstrated NGS chimerism detected emerging recipient fractions earlier than STR and with greater reproducibility across the range.²¹

The ASHI Engraftment Monitoring (EMO) Summary Report of participating laboratories also produced several key findings:

• NGS methods demonstrated substantially less inter-laboratory variability than STR.
• Across all chimerism levels, but especially 0.1 to 10%, NGS had far fewer discrepant results.

The report indicates that NGS was better suited for detecting incremental chimerism changes, more accurately identifying relapse risk or treatment response. This is a rare and strong profession-wide endorsement for a methodological transition away from STR-based chimerism. ²²

Key messages found across multiple studies were that lineage-specific IMC often preceded relapse by 2 to 4 weeks, ddPCR/NGS frequently detected IMC days to weeks earlier than qPCR, and that IMC rises as low as 0.05 to 0.1% had clinical significance. The earlier detection offered by ddPCR and NGS techniques is meaningful since patient interventions, such as DLI, work best before disease burden escalates.

Literature Review Limitations

Several well-cited studies included limited sample sizes (n<65), mixed disease groups, variable conditioning regimens, and non-uniform sampling schedules. While these reduced their individual statistical power, the reproducibility of findings across different countries, technologies, platforms, and disease groups reinforces the overall conclusion. Notably, studies with larger cohorts demonstrated consistent patterns which align with earlier smaller studies, supporting their credibility.

Another major challenge in evaluating the evidence base above was the lack of standardisation around what constitutes a clinically meaningful change. Different studies used absolute thresholds (≥0.1%, ≥0.05%), dynamic changes (doubling or sequential rises), lineage-specific increases, and mixed lineage discordance (e.g. CD33⁺ IMC despite stable whole blood chimerism). This heterogeneity complicates cross-study comparison and should be explored further. However, it was consistently shown that rising recipient DNA is clinically meaningful and often precedes overt relapse or graft failure.

Several studies recommended implementing a harmonised set of definitions for measuring IMC; adopting this would improve comparability between centres and support evidence-based clinical decisions. ²¹ ²³ One suggested schema for this (drawn from the findings across the studies above) is detailed in the table below, which aligns well with the sensitivity capabilities of dPCR/NGS technologies:

 

Table 2. Possible cutoffs for defining IMC within the microchimerism range.

 

These cutoffs may help identify clinically relevant IMC earlier, enabling clinicians to act during the window of highest therapeutic leverage. Recommended pathways may include reduction or withdrawal of immunosuppression, DLI, complementary testing such as measurable residual disease (MRD), targeted therapies (e.g., FLT3 inhibitors in FLT3-ITD positive AML), or increasing the frequency of chimerism surveillance. Embedding microchimerism-sensitive chimerism into HSCT aftercare protocols can significantly reduce the risk of late relapse by allowing pre-emptive therapy earlier in the disease kinetics.

Conclusion

Microchimerism-sensitive technologies, including NGS and dPCR, represent a transformative improvement in post-transplant surveillance. They allow earlier detection of relapse, enable pre-emptive interventions that alter clinical trajectories, and provide more reproducible, standardisable data between laboratories. Combined with lineage-specific analysis, these methods offer unparalleled insight into graft dynamics and disease biology.

The collective evidence supports an urgent shift toward microchimerism-sensitive chimerism monitoring in HSCT. Adoption of NGS and ddPCR methods will:

• Improve early relapse detection.
• Reduce inter-laboratory variability.
• Support lineage-specific insights.
• Support more effective clinical interventions.
• Modernise transplant follow-up to align with the capabilities of molecular diagnostics.

The transition away from STR is not just an upgrade; it represents a fundamental improvement in patient care, backed by strong scientific validation.

With strong evidence, professional consensus (ASHI EMO), and increasing clinical adoption, the transition from STR to NGS is both scientifically justified and operationally achievable through leveraging existing molecular infrastructure. Microchimerism itself is not simply a technical enhancement; it represents a fundamental improvement in patient care, backed by strong scientific validation.

 

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