Frontiers in noninvasive diagnosis of kidney transplant rejection: from molecular messengers to functional imaging

Biological mechanisms and release kinetics

The cfDNA consists of double-stranded DNA fragments released into the systemic circulation during the processes of cell apoptosis or necrosis. These fragments typically display a length distribution ranging from 150 to 200 base pairs (bp) which reflects the characteristic feature of nucleosome protection [17]. In renal transplant recipients, circulating cfDNA comprises two distinct components. The vast majority originates from the turnover of the recipient’s own cells, particularly those of the hematopoietic system, and is termed recipient-derived cfDNA. Conversely, a minute fraction is derived from the death of grafted kidney cells and is referred to as dd-cfDNA [18]. Under stable conditions characterized by immune quiescence, the turnover rate of donor renal cells is minimal and the fraction of dd-cfDNA within the total cfDNA pool typically remains below 1% or even falls under 0.5%. However, during episodes of rejection encompassing both ABMR and TCMR, immune-mediated attacks induce extensive apoptosis and necrosis in allograft cells such as endothelial cells and renal tubular epithelial cells. This injury precipitates a sharp increase in the rate of dd-cfDNA release into the bloodstream [19]. A distinct advantage of dd-cfDNA lies in its rapid kinetic profile. The half-life of cfDNA in the blood is extremely short and ranges from only 30 to 60 minutes as it is cleared primarily through hepatic metabolism and renal excretion [20]. Consequently, dd-cfDNA is capable of reflecting the current injury status of the allograft in near real-time. In contrast, elevations in sCr often require days or even weeks to accumulate and resolve slowly even after the cessation of injury. Functioning as a real-time injury marker, changes in dd-cfDNA levels can be utilized to monitor the efficacy of antirejection therapies where effective treatment is typically signaled by a rapid decline in dd-cfDNA levels [21].

Detection technologies

Currently, the primary technical challenge in detecting trace amounts of dd-cfDNA in the blood lies in achieving high-sensitivity differentiation against the substantial background noise of recipient DNA. Mainstream technologies employed for this purpose primarily rely on two methodological approaches including targeted next-generation sequencing and droplet digital polymerase chain reaction (PCR). Targeted next-generation sequencing represents the most widely applied commercial pathway and operates based on genotypic disparities between the donor and recipient at single-nucleotide polymorphism (SNP) loci. This technique involves designing a pool of probes covering hundreds to thousands of high-frequency heterozygous SNP sites to perform targeted enrichment and sequencing of cfDNA in plasma [22]. Subsequently, bioinformatics algorithms analyze the allele frequencies within the sequencing reads to accurately calculate the proportion of donor alleles. A significant advantage of this method lies in its ability to function without the prior acquisition of donor genetic samples which makes it particularly suitable for scenarios such as deceased donor transplantation. Additionally, it features high-throughput capabilities that allow for the parallel processing of large sample volumes. However, the turnaround time for detection typically spans 2 to 3 days, costs are relatively high, and the process imposes substantial demands on downstream bioinformatics analysis capabilities [23].

Another pivotal technology is droplet digital PCR. This method utilizes microfluidic technology to partition the PCR reaction system into tens of thousands of nanoliter-sized droplets so that each droplet contains either zero or one target DNA molecule. Through endpoint fluorescence detection of all droplets, the absolute copy number of the target molecules is calculated precisely based on the principles of the Poisson distribution [24]. This technology boasts extremely high sensitivity capable of detecting dd-cfDNA fractions as low as 0.1% while providing results within hours at a relatively lower cost. Furthermore, it can simultaneously determine both the fractional abundance and the absolute concentration of dd-cfDNA [25]. Its limitation lies in the general requirement to design primers for specific high-frequency insertion-deletions or SNP sites which may depend on known donor and recipient genotype information or require the use of universal multi-locus kits.

Clinical validation and diagnostic efficacy

The clinical validity of dd-cfDNA has been robustly supported by multiple large-scale multicenter prospective studies which have established it as a pivotal noninvasive biomarker for the diagnosis of allograft rejection. The DART study stands as a landmark investigation establishing the diagnostic value of dd-cfDNA in differentiating types of acute rejection (AR). Data from this study demonstrated the exceptional performance of dd-cfDNA in identifying ABMR where median levels in patients with ABMR reached 2.9% significantly exceeding the 1.2% observed in patients with TCMR and the 0.3% found in the non-rejection control group [26]. A subsequent meta-analysis pooling data from 12 studies further confirmed this finding by reporting a pooled area under the curve (AUC) of 0.87 for the diagnosis of ABMR with sensitivity and specificity reaching 0.81 and 0.80, respectively [27]. In contrast, the diagnostic efficacy of dd-cfDNA for TCMR is relatively limited, particularly for low-grade lesions where the AUC ranges from approximately 0.71 to 0.73. This disparity may be attributed to the fact that TCMR primarily causes focal tubular injury resulting in a lower quantity of DNA released into the blood whereas ABMR directly damages the vascular endothelium leading to a greater influx of DNA into the circulation.

Beyond immediate diagnosis, dd-cfDNA has also demonstrated significant value in predicting long-term allograft function. The ADMIRAL study longitudinally monitored 1,092 patients and found that dd-cfDNA levels exceeding 0.5% were significantly associated with subsequent declines in eGFR. Persistently elevated dd-cfDNA levels nearly doubled the risk of a 25% decline in eGFR within 3 years posttransplantation which supports its utility as a long-term monitoring tool for identifying patients at high risk of subclinical injury [28]. The TRIFECTA study provided critical evidence regarding the biological basis of dd-cfDNA by prospectively collecting a large scale of paired samples. This study confirmed for the first time that plasma dd-cfDNA levels correlate strongly with molecular rejection phenotypes found in allograft biopsies, particularly in cases of active ABMR and mixed rejection where the association was even superior to traditional histological assessment [29]. This marks the evolution of dd-cfDNA from a mere marker of injury to a biological indicator directly linked to immune rejection activity. Recent large-scale multicenter evidence has further strengthened the clinical utility of dd-cfDNA. A large observational study demonstrated that dd-cfDNA is independently associated with allograft rejection and significantly improves the discriminative performance of standard clinical models, with AUC increasing from 0.777 to 0.821 [30]. Beyond its role as a standalone biomarker, subsequent studies have explored its application in clinical stratification and highlighted the value of integrating dd-cfDNA with immune markers. For example, a prospective study showed that combining dd-cfDNA at a threshold greater than 0.4% with donor-specific antibodies significantly increased the specificity for diagnosing ABMR to 90.7% [31]. Collectively, these findings support the incorporation of dd-cfDNA into multiparametric diagnostic frameworks to enhance the precision of clinical assessment.

Critical controversies and frontier advances

Although the reporting of dd-cfDNA results currently relies primarily on the fraction of total cfDNA as a core metric with clinical cutoffs typically set at 1.0% or 0.5%, this fractional index suffers from inherent mathematical limitations [32]. As a relative ratio, its value is influenced not only by the numerator representing the quantity of dd-cfDNA molecules derived from allograft injury but is also highly susceptible to interference from fluctuations in the denominator representing the recipient’s own cfDNA levels. For instance, during episodes of infection or physiological stress in the recipient, a surge in cfDNA released by autologous leukocytes can dilute the dd-cfDNA fraction and lead to false-negative results, whereas a reduction in total cfDNA in the context of leukopenia can cause a spurious elevation in the fraction and result in false positives [33]. To address this deficiency, the academic community is increasingly advocating for the adoption of absolute quantification as a complementary or alternative metric. Studies indicate that measuring the absolute concentration of dd-cfDNA offers superior sensitivity compared to using the fraction alone in certain scenarios [34]. Furthermore, a recent study proposed an innovative dual-positive diagnostic strategy which requires both a dd-cfDNA fraction exceeding 1.08% and an absolute copy number greater than 32 cp/mL. This strategy elevated diagnostic specificity to 97.14% and significantly optimized the positive predictive value which suggests that future clinical interpretation standards may evolve toward this composite model [35].

It is imperative to clarify that dd-cfDNA serves fundamentally as a marker of allograft injury rather than a specific indicator of rejection. Any pathological process resulting in allograft cell injury or death including BK virus nephropathy, acute tubular necrosis (ATN), or severe systemic infection may precipitate an elevation in its levels [36]. Consequently, its primary clinical utility resides in its exceptionally high negative predictive value which allows it to serve as a reliable exclusionary tool. When dd-cfDNA levels remain low, clinicians can proceed with greater confidence in avoiding unnecessary biopsies. Conversely, elevated levels necessitate a comprehensive assessment integrated with donor-specific antibody status, clinical presentation, and other noninvasive biomarkers while renal biopsy remains requisite for the definitive determination of etiology when indicated. In addition, methodological factors should be considered when interpreting dd-cfDNA results. Differences between fractional and absolute quantification approaches may influence clinical interpretation, as these metrics reflect distinct biological aspects and may be differentially affected by systemic conditions. Furthermore, variability in cutoff values across platforms and studies remains an important limitation, which may hinder standardization and broader clinical implementation.

Another limitation of dd-cfDNA worth considering is that the interpretability of results is reduced in cases of multi-organ transplantation from the same donor. In such situations, currently available detection methods cannot distinguish the tissue origin of DNA fragments derived from the donor [37]. Consequently, elevated dd-cfDNA levels reflect the total burden of injury across all transplanted organs rather than providing organ-specific information. In the presence of multiple allografts, this limitation significantly restricts its clinical utility in diagnosing renal rejection. Emerging research approaches may help address this challenge. For example, recent studies have explored tissue-specific DNA methylation patterns, fragment size profiles, and nucleosome localization characteristics to achieve more precise attribution of cfDNA to its source organ [38]. Although these techniques are currently primarily in the research phase, they hold promise for improving the specificity and clinical utility of dd-cfDNA in complex transplant settings.

Immunobiology of the CXCL9/CXCL10-CXCR3 axis

CXCL9, also known as monokine induced by gamma interferon, and CXCL10, known as interferon-gamma-inducible protein 10 (IP-10), belong to the CXC chemokine family and exert their biological functions by binding to the CXCR3 receptor [39]. CXCR3 is predominantly expressed on the surface of activated Th1 cells, CD8+ cytotoxic T cells, and natural killer cells. During the initiation phase of the rejection cascade, antigen-presenting cells recognize alloantigens and subsequently activate T cells [40]. These activated T cells infiltrate the allograft tissue and release interferon-gamma (IFN-γ). Functioning as a potent pro-inflammatory cytokine, IFN-γ induces renal tubular epithelial cells and microvascular endothelial cells to synthesize and secrete copious amounts of CXCL9 and CXCL10 [41]. These chemokines are excreted into the urine while simultaneously establishing a concentration gradient that recruits additional CXCR3+ immune cells into the allograft, thereby creating a positive feedback loop of amplification that manifests as tubulitis and endothelitis [42]. Since CXCL9 and CXCL10 serve as critical mediators in the early phases of the immune response, their elevation in urine typically precedes alterations in sCr and the formation of histological damage, which confers significant early warning value to these biomarkers [43].

Diagnostic thresholds and clinical efficacy

Clinical guidelines issued by the ESOT recommend urinary chemokines as useful noninvasive tools in specific clinical contexts. In patients with stable graft function, urinary CXCL9 and CXCL10 can assist in excluding subclinical rejection, whereas in patients with graft dysfunction, they may serve as adjunctive biomarkers to support the diagnosis of AR [13].

The clinical utility of urinary chemokines has been supported by multiple lines of evidence. Early studies using urinary-cell messenger RNA (mRNA) profiling identified a three-gene signature consisting of CD3ε, CXCL10 (IP-10), and 18S ribosomal RNA for the noninvasive diagnosis of acute cellular rejection, highlighting the role of CXCL10 at the transcript level [44]. Subsequent clinical studies, including the CTOT-01 trial, further demonstrated that urinary CXCL9 protein levels can serve as an early diagnostic and predictive biomarker, with elevations preceding clinical rejection by several weeks [45].

In clinical practice, urinary chemokine levels are typically normalized to urinary creatinine to account for variations in urine concentration. Recent studies have reported that CXCL10/creatinine and CXCL9/creatinine ratios show moderate diagnostic performance, with AUC values around 0.7 and established cutoff values for clinical interpretation [46]. In addition to diagnostic utility, elevated urinary chemokine levels have been associated with adverse graft outcomes, including progression to graft dysfunction and long-term allograft loss.

Limitations and differential diagnosis

Similar to dd-cfDNA, the specificity of urinary chemokines is compromised by the presence of other inflammatory states. For instance, infections with the BK virus or cytomegalovirus activate robust Th1-type immune responses and induce the release of IFN-γ. This cascade leads to significantly elevated levels of urinary CXCL9 and CXCL10 which can sometimes exceed those observed in patients with allograft rejection [47]. Consequently, the interpretation of abnormally elevated urinary chemokines necessitates the prior exclusion of active viral infections via PCR testing. Furthermore, bacterial urinary tract infections including cystitis and pyelonephritis can also induce elevations in chemokine levels which requires a comprehensive differential diagnosis incorporating urinalysis and bacterial culture results to identify the underlying cause.

Unique advantages of urinary exosomes

Urinary exosomes predominantly originate from glomerular structures including podocytes and endothelial cells as well as renal tubular epithelial cells and immune cells infiltrating the kidney [49]. Unlike cell-free RNA, intra-exosomal RNA is shielded by a lipid bilayer which confers exceptional stability by protecting it against degradation from high concentrations of urinary RNases [50]. Research has demonstrated that exosomal mRNA remains intact even when urine samples are stored at 4 °C for 2 weeks, a feature that significantly facilitates sample collection and transportation [51].

Exosomal mRNA gene signatures

Leveraging high-throughput sequencing and machine learning (ML) screening, researchers have successfully established multiple exosomal transcriptomic signatures with diagnostic utility. For instance, a urinary exosomal mRNA detection assay developed on the Thermo Fisher/Exosome Diagnostics platform demonstrated in a validation study involving 175 patients that a multigene mRNA signature derived from exosomal transcriptomic profiling correlates highly with biopsy-proven rejection [52]. This signature is capable not only of accurately distinguishing rejection from non-rejection states with an AUC exceeding 0.90 but also of further differentiating between TCMR and ABMR. Furthermore, a simplified model based on six genes exhibited a negative predictive value as high as 90% for excluding ABMR which provides a substantial evidentiary basis for its clinical application [53].

Concurrently, exosomal miRNAs have also demonstrated immense diagnostic potential. Researchers have identified a triad miRNA signature consisting of hsa-miR-21-5p, hsa-miR-31-5p, and hsa-miR-4532 which achieved an AUC of 0.77 for diagnosing AR in a validation cohort and indicates promising application prospects [54]. Notably, the elevation of miR-21 levels which is closely associated with fibrosis pathways may serve as an early warning signal for chronic injury [55].

Blood gene expression profiles (Kidney Solid Organ Response Test)

The Kidney Solid Organ Response Test (kSORT) is a risk scoring system based on the expression levels of 17 genes in peripheral blood designed to evaluate the immune status of the recipient by distinguishing between immune quiescence and high-risk rejection [56]. Early data from the AART study indicated that kSORT achieved an AUC as high as 0.94 for predicting AR [57]. However, subsequent independent validation studies have reported more modest performance. For example, a recent study showed that the kSORT assay achieved an AUC of approximately 0.71, indicating only moderate predictive accuracy [58]. These discrepancies suggest that the predictive performance of kSORT may be less robust than initially reported and may vary across different clinical settings and patient populations. The prevailing consensus further indicates that peripheral blood transcriptomic biomarkers are susceptible to systemic nonspecific inflammatory signals, which may limit their organ specificity compared with urinary biomarkers.

Torque teno virus

Torque teno virus (TTV) is a nonpathogenic virus that is highly prevalent within healthy populations [59]. Its uniqueness lies in the fact that viral replication levels are directly influenced by the host’s immune status and are inversely correlated with the intensity of immunosuppression which leads to its recognition as an endogenous immune thermometer. Specifically, a higher TTV load suggests that immunosuppression may be excessive, thereby increasing the risk of infection, whereas a lower load may imply insufficient immunosuppression and a correspondingly elevated risk of rejection [60]. Currently, immune monitoring strategies based on TTV have advanced to the stage of prospective clinical trials such as the TTV-GUIDE IT study which aims to explore the dynamic adjustment of immunosuppressant dosages based on TTV loads to provide a novel pathway for achieving individualized precision immunotherapy [61].

Blood oxygen level-dependent magnetic resonance imaging: monitoring renal hypoxia

The underlying principle of blood oxygen level-dependent MRI (BOLD-MRI) rests upon the paramagnetic properties of deoxyhemoglobin. Deoxyhemoglobin induces local magnetic field inhomogeneities within the tissue which accelerates transverse relaxation and manifests as an increase in the effective transverse relaxation rate known as R2* [73]. Consequently, the R2* value is inversely correlated with tissue oxygen partial pressure where a higher R2* value typically indicates more severe tissue hypoxia [74].

In the context of renal allograft rejection, the application of BOLD-MRI has unveiled a complex phenomenon often described as an oxygenation paradox. While the vasculitis and edema accompanying AR theoretically restrict blood flow and induce tissue hypoxia, clinical studies have observed that renal medullary R2* levels may paradoxically decrease or remain unchanged during the early stages of rejection which suggests a relative improvement in oxygenation. The potential mechanism underlying this phenomenon is that renal oxygen consumption primarily supports the active reabsorption of sodium ions by the renal tubules. Tubulitis occurring in early rejection impairs tubular function and significantly reduces sodium reabsorption along with its requisite oxygen consumption. When the reduction in oxygen consumption exceeds the decline in oxygen supply caused by compromised blood flow, the actual oxygen content within the tissue rises relatively and manifests as a decrease in R2* values on BOLD-MRI [75]. Furthermore, BOLD-MRI provides a noninvasive measure of renal tissue oxygenation. Longitudinal assessment of stable kidney transplant recipients and their donors demonstrated that cortical and medullary R2* values can track changes in renal oxygenation over time, highlighting their potential utility in monitoring allograft physiology [76]. This unique feedback mechanism enables BOLD-MRI to sensitively detect early impairments in tubular function but simultaneously adds complexity to the interpretation of imaging results [77]. Therefore, to evaluate renal oxygenation regulation and reserve function more comprehensively, clinical practice often incorporates the furosemide stress test for integrated analysis.

Diffusion-weighted imaging: detecting inflammatory infiltration

Diffusion-weighted imaging (DWI) relies on the physical principle of applying diffusion-sensitizing gradient fields to measure the Brownian motion of water molecules within tissues and utilizes the apparent diffusion coefficient (ADC) for quantitative analysis. In the clinical context of renal allograft rejection, this technology demonstrates clear diagnostic value. During renal allograft rejection, the infiltration of the renal interstitium by large numbers of inflammatory cells, such as T cells and macrophages, together with accompanying cytotoxic edema, leads to a marked narrowing of the extracellular space. This process severely restricts the free diffusion of water molecules and characteristically manifests as a significant reduction in ADC values [78]. Previous studies have suggested that the diagnostic performance of DWI may be influenced by acquisition parameters such as b-values, with higher b-values potentially improving sensitivity to diffusion restriction [79]. However, according to a systematic review, current evidence indicates that although ADC values are associated with renal dysfunction and histopathological changes such as fibrosis, DWI remains limited in its ability to differentiate among the various underlying causes of allograft dysfunction, including rejection, ATN, and other injuries [80]. Instead, DWI appears to have greater utility in assessing the severity of renal impairment and microstructural alterations, rather than serving as a specific diagnostic tool for rejection.

Arterial spin labeling: contrast-free perfusion quantification

The physical principle underlying arterial spin labeling (ASL) involves the application of radiofrequency pulses to magnetically label water molecules within arterial blood, thereby utilizing them as endogenous tracers. Images are acquired as this labeled blood perfuses the kidney and are subsequently subtracted from control images obtained without labeling which allows for the precise calculation of renal blood flow [81]. This methodology completely obviates the need for exogenous gadolinium-based contrast agents and thereby eliminates the associated risk of nephrogenic systemic fibrosis and ensures a high safety profile. An initial study has demonstrated that renal cortical perfusion measured via ASL is significantly reduced in a patient experiencing AR and that this parameter exhibits a distinct correlation with the eGFR [82]. However, it is important to note that this reduction in perfusion is not inherently specific to rejection, as similar hemodynamic alterations were also observed in cases of allograft artery dissection and hydronephrosis within the same study. Furthermore, comparative research indicates that ASL may be a more promising imaging technique than BOLD-MRI for diagnosing renal allograft injury, as it provides a more sensitive assessment of cortical perfusion deficits [83]. While the potential exists to utilize both modalities to explore the pathophysiological phenomenon of perfusion-oxygenation mismatch, the superior diagnostic accuracy of ASL alone suggests it may be the more robust primary functional tool in this context. However, the feasibility of widespread clinical implementation, particularly in terms of cost-effectiveness and accessibility, requires further evaluation.