The gold standard for monitoring the health of solid organ transplants (SOT) has traditionally been through biopsy of the donor organ. Biopsies can be performed in response to suspicion of graft pathology (clinically indicated) or as part of a routine monitoring protocol (protocol or surveillance biopsies). Protocol biopsies are a form of screening test, and therefore must fulfill the criteria outlined for successful screening. They must be safe and acceptable to the patient, detect a clinical condition at a stage where intervention can change the course, and detect abnormalities sufficiently frequently to justify the cost and risks associated.
These criteria can be questioned for the monitoring of organ transplants. Biopsies represent an invasive procedure and are uncomfortable and inconvenient for patients. Large series of renal transplant protocol biopsies demonstrate a major complication rate of 1%, with a 3.5% risk of gross hematuria.1 Around 25% biopsies yield an inadequate specimen; this risk may be larger with a smaller needle size. With modern immunosuppression, detection of subclinical rejection may be too infrequent to justify these risks, and many units no longer perform routine biopsies.2 In nonrenal transplants, there is a lack of a reliable biochemical marker, equivalent to serum creatinine, to detect changes in graft function to guide clinically indicated biopsies. Similar biopsy complication rates are seen with endomyocardial biopsy after cardiac transplantation and transjugular liver biopsy,3,4 although protocol biopsies are more commonly used in these groups due to a higher potential for the detection of clinically relevant events and lack of alternative monitoring tools.
The disadvantages of histology for the routine monitoring of transplant organs have led to a great deal of interest in noninvasive strategies to detect graft injury and/or rejection. The ideal noninvasive test would be measureable in urine or plasma, relatively cheap for routine use, have a rapid turnaround, and be sensitive and specific for graft injury. Current commonly used methods include measurement of organ function where available (eg, serum creatinine), or therapeutic drug monitoring of immunosuppressive drugs as a surrogate for adequate immunosuppression and therefore rejection risk. More sophisticated strategies involve monitoring the level of immune system activity, such as nuclear factor of activated T cell–regulated gene expression, immune cell function assay or urinary/plasma chemokine levels.5-7 Alternatives include the measurement of damage-related gene expression in injured/rejecting organs (eg, Allomap or kSORT).8,9
One proposed method for detecting allograft injury is in the measurement of cell-free DNA (cfDNA) in the plasma or urine of transplant recipients. Presence of cfDNA was first identified by Mandel and Metais in 1948, and is released during apoptosis or necrosis in response to injury.10 Cell-free DNA assays have found use in prenatal diagnosis and in the detection and monitoring of malignancy.11,12 A number of groups have now investigated the use of cfDNA as a marker of transplant graft injury. In particular, the ability to differentiate recipient cfDNA and donor-derived cfDNA (dd-cfDNA) makes for a promising tool for the early and sensitive detection of allograft injury. Proof of concept has now been published for all solid organ types, and this study aims to systematically review the techniques and evidence for the relationship between dd-cfDNA levels and clinical outcomes in SOT recipients.
MATERIALS AND METHODS
Protocol and Registration
This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement.13 The protocol was prospectively registered with the International Prospective Register of Systematic Reviews (registration number CRD42017082273).
All studies that reported dd-cfDNA levels in the urine or plasma of adult or pediatric SOT recipients and related these levels to 1 or more transplant-related outcomes were eligible for inclusion. Recipients of cell or bone-marrow transplants were excluded, as were studies reporting laboratory techniques with no relationship to clinical outcomes of interest. All study designs were eligible for inclusion. No restrictions were placed on publication language or date.
A systematic literature search was performed in OVID MEDLINE and EMBASE, the Transplant Library, and the Cochrane Library for studies that met the inclusion criteria. Search terms included keywords and free text terms for solid organ transplantation and cfDNA (see SDC, Materials and Methods 1 for a sample search strategy, http://links.lww.com/TP/B643). The final date for searches was June 12, 2018. Reference lists of included studies and relevant reviews were screened for potentially relevant references not identified by the initial search.
To identify unpublished and ongoing studies, the clinicaltrials.gov, EudraCT and ISRCTN trial registries were searched using similar terms to the primary literature.
Duplicates were discarded from the initial search results. The remaining titles and abstracts were reviewed independently by 2 reviewers (S.K. and A.T.) to determine whether they met the inclusion criteria. Full articles of potentially relevant studies were reviewed before confirming their inclusion. Interreviewer agreement was assessed by means of percentage agreement and Cohen κ. Any discrepancies in inclusion were resolved by review and discussion between the authors.
Data Abstraction and Analysis
Studies are identified by the first author and year of the first full publication (if available) or published abstract. Study-level data including study design, population, quality assessment, organ type, patient and sample numbers, sample type (plasma/urine), laboratory methodology, and outcomes reported were extracted into a spreadsheet. Data relating dd-cfDNA to clinical outcomes were identified as acute rejection (AR), other transplant related outcomes and response to treatment. Studies that compared the diagnostic accuracy of dd-cfDNA to other markers were also identified. For studies that reported diagnostic test accuracy (DTA) data (eg, sensitivity, specificity, area under the received operator characteristic curve [ROC AUC], positive and negative predictive values), these data were extracted along with the threshold values used. All laboratory values are presented using the units recorded in the original manuscript.
We had initially planned to perform a DTA meta-analysis on studies that reported DTA data, but it became apparent that heterogeneity was too great and study quality too poor to allow reliable analysis. Therefore, all findings are reported in the form of a narrative review.
Risk of Bias in Individual Studies
In studies reporting DTA data, risk of bias was assessed using the Quality Assessment Tool for Diagnostic Accuracy Studies-2 tool.14 This validated instrument assesses the risk of bias resulting from patient selection, application of index and reference tests, patient flow and test timing. Two reviewers (S.K. and A.T.) independently performed the assessment, and any discrepancies were agreed by discussion.
Literature searches identified 4347 citations across all databases. 161 citations underwent full text review, with a total of 95 manuscripts/abstracts from 47 studies meeting the inclusion criteria (Figure 1). It is possible that there is some overlap between the patient cohorts in some studies as studies used samples from the same biobanks with different analysis methods. Trial registry searches identified 6 ongoing studies, 5 of which were actively recruiting (NCT02178943, NCT03326076, NCT02109575, NCT03255265, and NCT02423070). Two of these ongoing studies had preliminary results identified in the main literature search (NCT02178943 and NCT02424227). Interreviewer agreement was substantial - Cohen κ was 0.69 with 84.7% agreement.
Identified studies are detailed in Table 1. Of the 47 studies, 24 were reported in abstract form only. One study was a report of a single case, the rest were retrospective (n = 17) and prospective (n = 29) cohort studies. Thirty-eight studies were from single center cohorts, with 9 studies reporting on multicenter cohorts. Transplant types were kidney (n = 18), liver (n = 7), heart (n = 11), kidney-pancreas (n = 1) and lung (n = 5). Five studies analyzed samples from multiple transplant types. Nineteen studies reported data regarding DTA; no studies validated cfDNA as a test in a separate cohort.
For studies reporting DTA, risk of bias was variable across the Quality Assessment Tool for Diagnostic Accuracy Studies-2 domains (SDC, Materials and Methods 2,http://links.lww.com/TP/B643). No studies clearly predefined a threshold dd-cfDNA level for the diagnosis of clinical condition, risking overestimation of test accuracy. Patient populations in most studies were representative of the transplant population as a whole, although 4 studies retrospectively selected patients according to their clinical condition (rather than including consecutive patients), which again artificially increases test accuracy. The majority of studies used biopsy-proven AR (BPAR) as a reference standard.
All nonrenal transplant studies measured dd-cfDNA levels in plasma samples. Of the 18 kidney transplant studies, 12 measured dd-cfDNA in plasma, 3 in urine, and 3 in both urine and plasma.
Techniques for Detection of Donor-derived cfDNA
Although the extraction of cfDNA was fairly standard across studies, different methods for determining the donor-derived fraction of cfDNA were employed. The most straightforward method used in the included studies is the detection of the sex-determining region Y or testes-specific protein Y-linked Y-chromosome repeat in female recipients of male organs.31,32,39,53,81,102 Although simple to detect and not requiring donor material for genotyping, this limits dd-cfDNA quantification to a small fraction of transplant recipients, so it is not suitable for widespread use. A similar technique was used for known mismatches of the rhesus gene.54
A number of studies employed methods that allow differentiation of host and donor cfDNA in most, if not all, recipients. Two studies used amplification of HLA DNA with quantitative polymerase chain reaction (PCR) or digital droplet PCR (ddPCR), allowing identification of HLA alleles present in the donor but not the recipient.96,98 Recipient genotype can be determined from white blood cells with ddPCR. This works for the majority of recipients may be more challenging in closely related live donor/recipient pairs. Many of the recent studies identified made use of informative single nucleotide polymorphisms (SNPs) or deletion/insertion polymorphisms that are present in the donor but not the recipient. Selection of panels of polymorphisms that are known to be highly variable in the population of interest means that for most donor/recipient pairs, informative alleles will be present. These studies used quantitative PCR,57,59,75,92 ddPCR15,30,43,55,61,99,101 or massive parallel sequencing24 to detect informative SNPs. Although earlier studies required initial detection of SNPs in both donor and recipient samples to detect informative mismatches, more recent studies have used computational approaches to determine the minor donor type, removing the requirement for donor samples and typing.15,30,55,61,99,101
Stable Values and Time Course
Studies variably reported dd-cfDNA as the proportion of total cfDNA (n = 32), absolute DNA levels by weight (n = 4), copy numbers (n = 5) or as genomic equivalents/mL (n = 3). Twenty-one studies reported the time-course of dd-cfDNA levels in the immediate posttransplant period, all demonstrating a rapid fall to steady-state baseline levels in uncomplicated patients by around days 7 to 10 posttransplant. Studies comparing different organ types suggested that the decline in levels seen in cardiac transplant recipients is slower than that after liver transplantation.58 Initial posttransplant levels are also higher in deceased donor compared to live donor transplant recipients, in keeping with lower levels of graft injury in live donor organs.101
Steady-state plasma dd-cfDNA levels appear to vary by organ type. Mean fraction in liver (dd-cfDNA:total cfDNA range 3.3-5%) and lung (range, 2-5%) recipients is higher than that seen after cardiac (range 0.06-0.6%) and renal transplantation (range, 0.3-1.2%). This was confirmed in studies that directly compared recipient of different organ types using the same technique, with higher levels seen in liver transplant recipients compared to cardiac or renal transplants.99 The higher levels seen in lung and liver recipients most likely relate to a greater transplanted cell mass, a theory supported by the finding that recipients of double lung transplants have higher levels than recipients of single lungs.92 Dd-cfDNA fraction in the urine of renal transplant recipients was higher than that documented in plasma (8.7-55%).30,39 Cardiac transplant recipients with a left ventricular assist device (LVAD) pretransplant demonstrate higher dd-cfDNA levels than those without.79
Interestingly, De Vlaminck and colleagues reported a slow increase in dd-cfDNA levels in lung transplant recipients from 3 months onward, which they relate to the development of chronic damage related to a loss of lung function.92
Relationship to AR
Forty-one (85%) studies reported the relationship between dd-cfDNA levels and BPAR. All but 1 study reporting on kidney transplant recipients demonstrated significant elevations in dd-cfDNA levels at the time of BPAR. Bloom and colleagues16 demonstrated higher dd-cfDNA levels in antibody-mediated rejection (AMR) than T cell–mediated rejection (TCMR). In keeping with this, dd-cfDNA levels are also elevated in recipients developing de novo donor-specific antibodies (DSA).42 Combined diagnosis using DSA and cfDNA levels may improve diagnostic accuracy.17 Levels also appeared to correlate with the severity of TCMR, with no difference seen between mild rejection (Banff 1A) and controls. This finding was also reflected in the study from Sigdel et al,32 who demonstrated a correlation between dd-cfDNA levels and Banff i and t scores. Elevated levels were reported up to 31 weeks before the clinical diagnosis of AR in up to 68% of recipients.24,31,34 Lee and colleagues were the only group who did not find a relationship between either urine or plasma dd-cfDNA levels and presence of BPAR.30 The reason for this discrepancy is unclear, although the sample size in this retrospective study was very small, with high inter and intrapatient variability in dd-cfDNA levels seen. A single study in recipients of simultaneous kidney-pancreas transplant recipients demonstrated similar elevations of dd-cfDNA during episodes of rejection.
All studies in liver transplant recipients demonstrated elevated dd-cfDNA levels during episodes of BPAR. As with kidney transplant recipients, levels appear to rise before the clinical manifestations of AR, with 2 studies demonstrating elevated levels 4 to 6 days before an aminotransferase rise, and 8 to 15 days before biopsy confirmation of rejection.55,100
The majority of studies in cardiac transplant recipients found a relationship between AR (identified on endomyocardial biopsy) and dd-cfDNA levels. As with kidney transplant recipients, the relationship appears to be stronger for AMR and more severe TCMR than for mild TCMR.57,59,80,104 Again, elevated levels of dd-cfDNA precede the diagnosis of AR by up to 5 months.57,59 Of note, 1 study in pediatric recipients of cardiac transplants failed to identify a difference in dd-cfDNA levels between patients with AR or a stable course, albeit with small numbers of recipients experiencing AR episodes.75
A similar pattern was seen in lung-transplant recipients, with elevated levels of dd-cfDNA seen at the time of endobronchial biopsy demonstrating AR. As in kidney and cardiac rejection, levels related to the severity of rejection, with greater discriminatory power seen for severe rejection.83,84,92,104
A number of studies followed dd-cfDNA levels after successful treatment of AR, demonstrating a fall to baseline levels in most cases.15,29,31,43,68,98,101,103 In keeping with the short half-life of dd-cfDNA (less than 1 hour), the majority of studies demonstrated a rapid fall to baseline after successful treatment, However, the time taken to return to baseline was variable, with Bloom et al reporting persistently elevated levels at 1 month with a return to baseline after 2 to 3 months, perhaps indicating residual graft injury. At least in cardiac transplant recipients, rebound of dd-cfDNA levels after treatment is a poor prognostic indicator.77
Diagnostic Test Accuracy
Nineteen studies reported measures of DTA (Table 2). In general, these supported the overall findings from all studies; dd-cfDNA levels were able to predict AR with moderate to good performance (ROC AUCs ranging from 0.59 to 0.97). Predictive ability appears similar across all organ types, with better performance seen for higher-grade and AMR. Threshold values for the liver appeared higher than the other organ types. Negative predictive value was generally superior to positive predictive value, supporting the idea the dd-cfDNA is most useful for excluding graft injury in a stable patient.16
Sigdel et al32,33 demonstrated good performance for the detection of acute allograft injury in 2 studies, but were unable to differentiate the causes of injury (BK virus nephropathy, pyelonephritis or rejection). In keeping with this, Moreira et al31 demonstrated improved discriminatory performance for rejection when procalcitonin levels were used in conjunction with dd-cfDNA to differentiate between infection and rejection.
Relationship Between Dd-cfDNA and Other Clinical Events
As suggested in the DTA data above, elevated dd-cfDNA levels were not always related to AR and elevations were seen in response to other causes of acute graft injury. In the kidney, elevated dd-cfDNA levels were seen with BK virus nephropathy and urinary tract infection/pyelonephritis.15,32,33,41 Much smaller rises were seen in recipients with acute tubular necrosis,15,31,33 and levels were unable to discriminate between normal histology and other chronic findings, such as calcineurin inhibitor toxicity or interstitial fibrosis/tubular atrophy.15,32 In liver recipients, levels elevate with active hepatitis B and C infection,44,53,55 but not with cholestasis.44,48,99 In lung recipients, elevated levels are seen in recipients with infections associated with chronic lung allograft dysfunction.85
A small number of studies attempted to relate baseline dd-cfDNA levels with long-term outcomes. In the kidney, Goh and colleagues demonstrated a positive correlation between dd-cfDNA levels at discharge from hospital and 1-year serum creatinine level.25 Similarly, Zhang and colleagues also identified a relationship between early dd-cfDNA levels and graft dysfunction at 12 months.40 In particular, a highly variable “peak-spiked” pattern of dd-cfDNA levels in the early posttransplant period was associated with long-term graft dysfunction, suggesting that repeated episodes of acute graft injury may impair long-term function.
There has also been suggestion that average dd-cfDNA levels over longer time periods may reflect cumulative graft injury and relate to longer-term adverse outcomes. In lung recipients, higher mean dd-cfDNA levels during the first 6 months after transplantation are associated with inferior survival and higher incidence of bronchiolitis obliterans syndrome.105 In cardiac recipients, high median levels associate with a combined endpoint of death, retransplantation, hemodynamic compromise or graft dysfunction at 3 years.62
Comparison With Other Markers
A few studies have compared dd-cfDNA with other markers of graft injury. It outperforms standard biochemical measures in both the kidney (serum creatinine) and liver (aminotransferases), with levels elevating earlier and providing better discrimination for AR.15,24,50,55
Two studies compared performance of dd-cfDNA levels with the Allomap score, a panel of gene assays used in the detection of AR.63,76 Little correlation is seen between the Allomap score and dd-cfDNA levels. Combining the 2 scores provided greater discriminatory power for the detection of AR in cardiac transplant recipients, suggesting that they may provide complementary information.
This systematic review has found evidence for the validity of dd-cfDNA as a biomarker in all SOT types. Donor-derived cfDNA can be reliably detected using a number of techniques and falls rapidly to a baseline level within 2 weeks of transplantation once the initial ischemia-reperfusion injury has subsided. Baseline levels vary between organ types, relating to the cellular mass of the organ transplanted, with highest levels seen in liver and lung transplantation. The majority of studies show a strong relationship with AR and other causes of acute allograft injury. Discriminatory power is greatest for more severe grades of AR and AMR, and levels return to baseline after successful treatment.
Donor-derived cfDNA meets many of the criteria required to be a useful screening test for AR. Levels have been shown to rise before the clinical manifestations of rejection, with elevated levels seen up to a month or more before diagnosis in some prospective studies. Refinement of the techniques for quantifying dd-cfDNA mean that it can now be quantified even in the absence of material for donor genotyping, and turn-around time once informative SNPs or alleles have been identified can be as short as 1 working day.100 These newer techniques also allow accurate detection of dd-cfDNA even in HLA-matched transplants.106
A recent study investigating dd-cfDNA as a diagnostic test in renal transplant recipients has demonstrated performance similar to the use of Troponin I in the diagnosis of acute myocardial infarction.107 Although intraindividual variability is generally lower than interindividual variability, there is some within-patient variation that must be considered when interpreting results. An increase of 61% or more from the previous value is likely to be clinically significant; smaller increases probably warrant a confirmatory test. Although similar in magnitude, the exact threshold for determining a “positive” test varied between studies even in the same organ type, likely reflecting both variability between populations and in the methods and assay used.
In general, studies included in this review identified a higher negative predictive value than positive, suggesting that the test may be most suited to excluding rejection when values are below the threshold. Levels are sensitive for graft injury, but not specific for the cause of injury, with elevated levels also seen in infections such as BK nephropathy and hepatitis. In reality, this means that elevated levels will need to be interpreted in conjunction with other clinical parameters and laboratory tests such as viral PCRs and urine culture. Indeed, the simple addition of procalcitonin as a marker of infection improves the specificity of dd-cfDNA in the setting of renal transplant rejection.31 In most settings, it is likely that dd-cfDNA will be used as a tool to identify the need for further investigation and to target protocol biopsies in the presence of subclinical changes, reducing the risks and costs associated with a protocol biopsy program while increasing yield. It will also find utility as a means of monitoring the response to treatment.
Although dd-cfDNA has largely been demonstrated as a marker for acute graft injury, there is also some evidence that elevated levels relate to inferior longer-term outcomes. In lung recipients, persistently elevated levels have been associated with chronic lung allograft dysfunction and bronchiolitis obliterans syndrome.85,105 In the kidney, persistently elevated and variable levels during the first 6 months posttransplant are associated with inferior graft function.40 This finding may in part be explained by underimmunosuppression, with low tacrolimus exposure being associated with higher dd-cfDNA levels possibly related to persistent immune activity and chronic graft damage.108
It must be noted that the majority of studies identified in this review are of limited methodological quality. All studies were retrospective or prospective cohorts, with a number of retrospective cohorts selecting patients based upon clinical manifestation of graft injury. Even in prospective studies, the gold standard test (biopsy) was often only applied in patients with clinical evidence of graft dysfunction, meaning that the utility of dd-cfDNA in detecting subclinical graft injury is uncertain. No studies attempted to validate the determined dd-cfDNA threshold in an external population, and no studies have attempted to determine the impact of prospective monitoring on clinical outcomes. Around half of the identified studies were reported in abstract form only. Although this is inevitable in such a rapidly expanding field, the limited space afforded in a conference abstract means that full methodological description is lacking and assessment of study quality is difficult.
It is not yet clear what is the optimum interval for dd-cfDNA measurement for routine transplant monitoring. Prospective studies identified in the present review used minimum intervals of 1 month between tests, with shorter intervals in the early posttransplant period when the risk of AR and infection are at their highest. This would seem reasonable given the finding that levels rise up to a month before clinically apparent organ damage.
Searches of trial registries identified a number of ongoing studies that may help to clarify some of these unanswered questions. The majority of ongoing studies are large, prospective multicenter cohort studies that will help to validate the thresholds to prompt further investigation and determine the optimum interval for monitoring. One study (NCT03326076) is aiming to test the clinical utility of routine and for-cause dd-cfDNA monitoring in renal transplant recipients, comparing clinical outcomes in patients undergoing monitoring with a matched retrospective control cohort in whom monitoring was not undertaken. This study will provide the first direct evidence as to whether dd-cfDNA monitoring can actually impact clinical outcomes.
Cell-free DNA may also have a role to play in assessing pretransplant injury and organ viability in deceased-donor transplantation. Methods have been described to determine the origin of circulating cfDNA using organ-specific methylation patterns.109 Use of beta cell-specific cfDNA detection has already been reported in the context of clinical islet cell transplantation.110 Application of these techniques in organ donors may allow the quantification of organ injury before procurement, aiding decisions where acute organ dysfunction is present. A recent abstract has provided proof of principle for this concept, with donor plasma mitochondrial DNA levels independently predicting slow-, delayed- and primary non-graft function after renal transplantation.111 Measurement of cfDNA levels during normothermic machine preservation may also help in pretransplant viability assessment. A recent study exploring perfusate cfDNA levels during ex vivo lung perfusion demonstrated significantly higher levels after 4 hours of perfusion in patients experiencing posttransplant graft dysfunction.112
In summary, donor-derived cfDNA shows promise as a biomarker for the detection of acute transplant graft injury. It has potential to reduce the need for protocol biopsy surveillance, allowing for a more targeted diagnostic approach. Detection of injury occurs before clinical manifestation, meaning that there is a window for earlier detection and treatment of AR and other causes of graft injury with the potential to improve outcomes. It may also facilitate the detection of underimmunosuppression and find use as a tool for monitoring during immunosuppression minimization. Further studies are required to validate the thresholds for further investigation and intervention, determine the optimum frequency for monitoring, and to identify whether prospective monitoring using dd-cfDNA can indeed improve transplant outcomes compared to current practice.
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