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Donor fraction cell-free DNA and rejection in adult and pediatric heart transplantation
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Donor Fraction Cell-Free DNA and Rejection in Adult and Pediatric Heart Transplantation Marc E Richmond MD, MS , Steven D Zangwill MD , Steven J Kindel MD , Shriprasad R Deshpande MBBS, MS , Jacob N Schroder MD , David P Bichell MD , Kenneth R Knecht MD , William T Mahle MD , Mark A Wigger MD , Nunzio A Gaglianello MD , Elfriede Pahl MD , Pippa M Simpson PhD , Mahua Dasgupta MS , Paula E North MD, PhD , Mats Hidestrand PhD , Aoy Tomita-Mitchell PhD , Michael E Mitchell MD PII: DOI: Reference:
S1053-2498(19)31767-X https://doi.org/10.1016/j.healun.2019.11.015 HEALUN 7044
To appear in:
Journal of Heart and Lung Transplantation
Please cite this article as: Marc E Richmond MD, MS , Steven D Zangwill MD , Steven J Kindel MD , Shriprasad R Deshpande MBBS, MS , Jacob N Schroder MD , David P Bichell MD , Kenneth R Knecht MD , William T Mahle MD , Mark A Wigger MD , Nunzio A Gaglianello MD , Elfriede Pahl MD , Pippa M Simpson PhD , Mahua Dasgupta MS , Paula E North MD, PhD , Mats Hidestrand PhD , Aoy Tomita-Mitchell PhD , Michael E Mitchell MD , Donor Fraction CellFree DNA and Rejection in Adult and Pediatric Heart Transplantation, Journal of Heart and Lung Transplantation (2019), doi: https://doi.org/10.1016/j.healun.2019.11.015
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Donor Fraction Cell-Free DNA and Rejection in Adult and Pediatric Heart Transplantation
-Marc E Richmond MD, MS, Department of Pediatrics, Division of Pediatric Cardiology, College of Physicians and Surgeons, Columbia University, New York, NY -Steven D Zangwill MD, Division of Cardiology, Phoenix Children’s Hospital, University of Arizona College of Medicine, Phoenix AZ -Steven J Kindel MD, Division of Pediatric Cardiology, Department of Pediatrics, Medical College of Wisconsin, Herma Heart Institute, Children’s Hospital of Wisconsin, Milwaukee WI -Shriprasad R Deshpande MBBS, MS, Division of Cardiology and Division of Cardiac Intensive Care, Children’s National Hospital, Washington DC -Jacob N Schroder MD, Division of Cardiovascular and Thoracic Surgery, Department of Surgery, Duke University, Durham NC -David P Bichell MD, Division of Pediatric Cardiac Surgery, Department of Surgery, Vanderbilt University, Nashville TN -Kenneth R Knecht MD, Department of Pediatrics, Arkansas Children’s Hospital Little Rock AR -William T Mahle MD, Division of Cardiology, Department of Pediatrics, Emory University, Children’s Healthcare of Atlanta, Atlanta GA -Mark A Wigger MD, Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University, Nashville TN -Nunzio A Gaglianello MD, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI -Elfriede Pahl MD, Division of Cardiology, Department of Pediatrics, Ann & Robert H. Lurie Children’s Hospital Chicago, Chicago, IL
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-Pippa M Simpson PhD, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI -Mahua Dasgupta MS, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI -Paula E North MD, PhD, Department of Pathology, Medical College of Wisconsin, Children’s Hospital of Wisconsin, Milwaukee, WI -Mats Hidestrand PhD, Department of Surgery, Medical College of Wisconsin, WI -Aoy Tomita-Mitchell PhD, Division of Pediatric Cardiothoracic Surgery, Department of Surgery, Medical College of Wisconsin, Herma Heart Institute, Milwaukee, WI -Michael E Mitchell MD, Division of Pediatric Cardiothoracic Surgery, Department of Surgery, Medical College of Wisconsin, Herma Heart Institute, Children’s Hospital of Wisconsin, Milwaukee WI Corresponding Author: Michael E. Mitchell, Herma Heart Institute, Medical College of Wisconsin, Children’s Hospital of Wisconsin, 9000 West Wisconsin Avenue, Milwaukee, WI 53226. Telephone: 414-266-2491, Fax: 414-266-2075. Reprint Requests: Michael E. Mitchell, Herma Heart Institute, Medical College of Wisconsin, Children’s Hospital of Wisconsin, 9000 West Wisconsin Avenue, Milwaukee, Wisconsin, 53226. Telephone: 414266-2491, Fax: 414-266-2075. Email address: [email protected] Keywords: Rejection, Non-invasive detection, Cell-free DNA, Heart transplantation, Pediatric heart transplantation Abstract Word Count: 248 Manuscript Word Count: 3402 Abstract:
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Purpose: Endomyocardial biopsy (EMB) is the current standard for rejection surveillance in heart transplant recipients. Quantification of donor-specific cell-free DNA (cfDNA) may be an appropriate biomarker for non-invasive rejection surveillance. A multi-center prospective blinded study (DNA-based Transplant Rejection Test, DTRT) investigated the value of donor fraction (DF), defined as the ratio of cfDNA specific to the transplanted organ to total amount of cfDNA present in a blood sample. Methods: 241 heart transplant patients were recruited from seven centers. Age at transplant ranged from 8 days to 73 years, with 146 subjects <18 years and 95 ≥ 18 years. All patients were followed for at least one year, with blood samples drawn at routine and for-cause biopsies. 624 biopsy-paired samples were included for analysis via a commercially available cfDNA assay (myTAIHEART®, TAI Diagnostics, Inc). Blinded analysis of repeated measures compared outcomes using receiver operating characteristic (ROC) curves. All primary clinical endpoints were monitored at 100%. All analysis and conclusions were reviewed by both an independent external oversight committee and the NIH mandated DTRT steering committee. Results: DF in ACR 1R/2R (n=15) was higher than ACR 0R (n=42) (p=0.02); DF in pAMR1 (n=8) and pAMR2 (n=12) (p=0.05) were higher than pAMR0 (n=466) (p=0.04 and p=0.05 respectively). By ROC analysis an optimal DF threshold was determined which ruled out the presence of either ACR or AMR. Conclusion: Cell-free DNA donor fraction holds promise as a non-invasive diagnostic test to rule out acute rejection in both adult and pediatric heart transplant populations.
Background: Despite the overall success of heart transplantation as a definitive treatment for end stage heart failure in adults and children, acute allograft rejection remains a major cause of morbidity and mortality. The use of non-invasive surveillance methods for rejection has been of interest to the heart transplant community since the first transplant in 1967. However, no non-invasive test has yet replaced
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endomyocardial biopsy (EMB) as the first line in rejection surveillance. In several recent studies, levels of donor-specific cell-free DNA (cfDNA) in the blood of patients who are experiencing allograft rejection have been shown to correlate with rejection1-3. Our group has previously described the relationship of the ratio of donor-specific cfDNA to total cfDNA, or donor fraction (DF), to acute cellular rejection (ACR) in a pilot study of 158 samples from 88 subjects at a single center3. The current study was designed as a large prospective multi-center observational study of both adult and pediatric heart transplant recipients examining in more detail the assessment of DF cfDNA post-transplant and its utility in predicting graft health. This report focuses on the association between elevated DF and the presence of EMB-confirmed allograft rejection. Methods: A prospective observational study (DNA-Based Transplant Rejection Test (DTRT)) was conducted among seven established heart transplant centers; each obtaining local Institutional Review Board (CHW 10/83, GC 111, CTSI 906) approval. Informed consent was obtained from all subjects prior to onset of study activities transplantation for this minimal risk study. Inclusion and exclusion criteria are listed in Table 1. Clinical information collected included patient demographics and clinical data throughout the admission for transplant, around treatment episodes for rejection, around all symptomatic and asymptomatic biopsies, and around all hospital readmissions. Date and exact time of EMB were checked against blood sample date and time to ensure that all analyzed blood samples were taken prior to any intra-cardiac access, as we have shown that the local trauma of biopsy leads to an acute elevation of cfDNA DF4. Local reads for EMB, hemodynamics at catheterization, echocardiograms, and coronary angiography performed for clinical purposes during the study period were recorded. Dates and times of all critical clinical events were recorded. If a subject was diagnosed with cancer or post-transplant lymphoproliferative disease, or became pregnant, the first dates of diagnosis were recorded, and they were excluded from analysis as these conditions introduce a confounding source of additional “non-self”
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cfDNA (Figure 1 and Table 1). The pathology reports of all biopsies were reviewed and 2004 ISHLT grade was recorded, with biopsy-proven acute cellular rejection (ACR) defined as Grade 1R or higher and biopsy-proven antibody-mediated rejection (AMR) defined as pAMR1 or higher. Results of all coronary angiography during the study period were recorded and graded according to the 2010 ISHLT grading system5 with a cardiac allograft vasculopathy (CAV) grade 1 or higher being defined as the presence of CAV5. Blood sample collection and shipping: Blood samples were obtained from heart transplant recipients in the following clinical scenarios: prior to transplant, days 1, 4, and 7 following transplant, and at discharge from transplant hospitalization; within 24 hours prior to cardiac catheterization; within 24 hours prior to and then days 1, 4, 7, 14, and 28 after initiation of treatment for rejection; at hospital readmission and again prior to discharge if the patient had been treated for either infection or rejection during the readmission. Initially, all patient blood samples for circulating cfDNA determination were collected as whole blood with a typical collection protocol6-9 in 10 ml Cell-Free DNA Blood Collection Tubes (BCT) (Streck, Omaha, NE) herein termed “whole blood-protocol” and immediately coded, de-identified, and delivered within 0-5 days to the CAP and CLIA accredited Children’s Research Institute (CRI) Nucleic Acid Extraction Laboratory (Milwaukee, WI), for plasma isolation and storage prior to cfDNA extraction. Shipping of these samples was accomplished by overnight delivery. Samples were packaged inside a protective pouch with a MicroDL logger (Marathon, San Leandro, CA) to record temperature every five minutes during shipment. The pouch was placed inside an insulated box packed with gel packs properly primed for the seasonal conditions to maintain ambient temperature throughout shipment. As the study commenced an issue was noted with shipment of whole blood specimens: preextraction lysis of leukocytes was occurring despite the presence of a cell membrane stabilizing agent in the collection tube. Enough genomic leukocyte DNA could be released to dilute the DF. To address this, the sample processing protocol was modified to require blood sample centrifugation to separate plasma
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rapidly at the local site of collection, herein termed “plasma-protocol”. Isolated plasma was frozen and then shipped on dry ice to the CRI extraction facility for subsequent cfDNA extraction prior to DF determination at the CAP and CLIA accredited TAI Diagnostics Clinical Reference Laboratory (Wauwatosa, WI). A novel quality assurance protocol based on cfDNA fragmentation analysis was developed to detect problematic post-collection leukocyte lysis so that any samples with evidence of leukocyte lysis above a conservative cut-off level could be rejected from the study in an unbiased manner10. Plasma processing and DNA extraction: Extraction of cfDNA from plasma collected from either the whole blood-protocol or plasma-protocol was performed using a ReliaPrepTM HT Circulating Nucleic Acid Kit, Custom (Promega, Madison, WI)10. Recipient and donor genomic DNA from buffy coats prepared from these samples were extracted by using ReliaPrepTM Large Volume gDNA Isolation System (Promega)10. Donor genomic DNA from tissue was extracted by using QIAamp DNA Micro Kit (Qiagen, Germantown, MD)10. Total cfDNA analysis: Total cfDNA (TCF) concentration of the plasma samples, including those collected under both whole blood and plasma protocols were measured by quantitative real-time PCR9. DF Analysis: Donor-specific cfDNA is calculated as a fraction (DF) of the total cfDNA and is performed without the requirement of a donor sample (myTAIHEART)3,10. The test quantitatively genotypes (qGT) a panel of 94 high frequency SNPs selected for their ability to reliably discriminate between alleles offering a rapid, non-invasive, high-throughput, and cost-effective manner to determine donor-specific cfDNA in the clinical transplant setting10. Briefly, sample cfDNA (15 ng) is spiked with an exogenous internal control and amplified by high-fidelity PCR as a multiplexed library followed by qGT10. In addition, recipient genomic DNA is extracted from leukocytes from a separate whole blood sample and analyzed with a “basic genotyping” (bGT) algorithm10.
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Clinical Data Collection: Clinical, laboratory, cardiac catheterization and echocardiographic data were recorded and data were managed using Research Electronic Data Capture (REDCap) tools hosted at the Medical College of Wisconsin (MCW, Milwaukee, WI)11. Monitoring: A risk-based approach was utilized to monitor the extensive database including one hundred percent monitoring of data fields required for the analysis of primary endpoints and spot monitoring of other data fields. Statistical Methods: Median DF cfDNA levels and interquartile ranges (IQR) are reported. To take account of the repeated measures, a generalized estimating equation model was used12,13. Generalized estimating equation (GEE) allowed for repeated measures12,13 in comparing across the rejection grades and performing ROC analysis. Subjects as clusters with logit link function and an autoregressive covariance structure was used. Due to the small sample size an unadjusted p value <0.05 was reported as significant. ROC curves were examined to assess the sensitivity and specificity of DF to compare its ability to distinguish healthy 0R vs 1R/2R14. A threshold value was chosen that maximized the sensitivity while allowing for reasonable specificity. Results were compiled for the whole blood-protocol, the plasmaprotocol, and for both collection protocols combined, with a sub analysis of pediatric subjects. Results: A total of 2537 samples were obtained during the study from 241 consented and transplanted individual subjects. For the specific purposes of this analysis with an aim to describe the relationship between DF and rejection as determined by EMB, ultimately 624 samples from 174 subjects were included after exclusions were applied (Figure 1). Clinical exclusions eliminated 970 samples and of those 1567 remaining, 429 were further excluded as they were not associated with EMB. This left a total of 1138 samples from 203 individual subjects. Before genotyping, 502 samples were excluded because of predefined quality control exclusions (Table 1, point 3). After genotyping but before unblinded
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analysis 12 samples were excluded for bioinformatic and sample quality QC (Table 1, point 4). This left 624 EMB associated samples from 174 individuals and formed the cohort for blinded analysis. Within the analytic cohort, 564 samples were drawn under the whole blood-protocol and 60 were collected using the plasma-protocol. Subject Demographics: Given the combined pediatric and adult subject group, the age at transplant of the 241 consented and transplanted subjects was 14.7 (3.4-50.6) years, with the youngest subject age 8 days at the time of transplant and the oldest 73.4 years. Pediatric patients (<18 years) comprised 60.0% of the total patient population (n=146). The population was mostly male (61.4 %), and the majority were of white race (65.6%), with 23.2% of subjects’ race reported as Black or African American. 10.8% of subjects reported Hispanic or Latino ethnicity. After exclusion criteria were applied to the sample and subject population, the final population demographics changed slightly with respect to age at transplant 16 (4.5-51.1) years, with a range of 56 days to 73.4 years. There were 101 (58%) pediatric patients (<18 years). The population for analysis remained predominantly male (63.2%) and white (66.7%), with 23.6% identifying as Black race and 9.8% of Hispanic or Latino ethnicity (Table 2). Whole Blood Protocol Analysis: Using samples collected under the whole blood-protocol we examined the relationship between DF and the presence of ACR. A total of 533 EMB associated samples were collected using the whole blood-protocol and included 357 with ACR 0R (healthy), 155 with ACR 1R and 21 with ACR 2R. In this analysis there was no difference in DF amongst the three groups (0.11% vs 0.12% vs 0.14%), nor was there a difference in DF between grade 0R and a composite group consisting of all samples associated with grade 1R or higher 0.11% vs 0.12%, p=0.56). Furthermore, ROC analysis revealed an AUC of only 0.525 in the whole blood group. We then sought to examine the relationship between DF and the presence of AMR using samples collected under the whole blood-protocol. A total of 466 samples were associated with biopsy read of
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pAMR0, with 8 showing pAMR1 (either pAMR1-i or pAMR 1-h) and 12 with pAMR2. In pairwise analysis of samples collected under the whole blood-protocol (Figure 2), there were significant differences in DF between the pAMR0 group and pAMR1 (p=0.04), as well as between pAMR0 and pAMR2 (p=0.05), however there was no statistical difference between pAMR1 and pAMR2 groups with respect to DF values (0.21% vs 0.30%, p=0.35). Since pAMR1 is a heterogeneous group consisting of both biopsies with evidence of immunohistochemical staining only (pAMR1i) as well as those with cellular edema without evidence of complement deposition (pAMR1h), the decision was made to treat pAMR2 as evidence of definitive acute antibody-mediated rejection. As such, when comparing samples from the whole blood protocol associated with pAMR2 vs those with healthy pAMR0 or pAMR1, pAMR2 was associated with a higher DF (0.30% vs 0.11%, p=0.04, Figure 3a). Using the predefined cutoff value of 0.3%, ROC analysis resulted in a sensitivity of 0.50 and a specificity of 0.88. Using the statistically optimized cutoff value of 0.19% resulted in improved performance; with a sensitivity of 0.92 and specificity of 0.75, yielding a NPV of 99.7% for the absence of pAMR2 or higher (Figure 3b). When further examining this relationship in the pediatric whole blood-protocol population only, 200 samples were associated with CR0 and 58 samples were associated with CR1/2. There was no significant difference between groups (p=0.71), and ROC analysis resulted in an AUC of 0.53, sensitivity of 0.76, specificity of 0.36, at a cutoff of 0.1. With respect to AMR in the pediatric whole blood-protocol population only, 239 healthy samples were associated with pAMR0 or pAMR1 while 11 samples were associated with pAMR2. There was a marginal difference in the DF between these groups with 0.13% in the pAMR0/1 group and 0.31% in the pAMR2 group (p=0.09, Figure 3c). ROC analysis with the same cutoff value of 0.19 determined from the full study population resulted in an AUC of 0.84, sensitivity of 1, specificity of 0.67 and a NPV of 100% for the absence of pAMR2 or higher (Figure 3d).
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Plasma Protocol Analysis: Concerned that the phenomenon of cell lysis was diluting the DF signal and impacting the ability to detect differences between samples with and without rejection, and more specifically ACR, the population of samples collected using the plasma-protocol were analyzed. Forty-two healthy plasma-protocol samples were associated with no cellular rejection (Grade 0R) and 15 were associated with ACR 1R or higher (14 grade 1R, 1 grade 2R). There was a significant difference in the DF between those samples associated with grade 1R or higher vs those without evidence of ACR (0.49% vs 0.10%, p=0.02, Figure 4a). ROC analysis of this population with a cutoff value of 0.3 resulted in sensitivity of 0.73, specificity of 0.93 and a NPV of 90.7% for the absence of ACR. Performance at the statistically optimized cutoff value of 0.23 was slightly improved with a sensitivity of 0.8, specificity of 0.88 and a NPV of 92.5%, (Figure 4b). Examining the relationship between DF and pAMR in the plasma-protocol samples there was a significant difference in the DF between those samples with pAMR 2 and those with pAMR 0 or 1 with a median DF of 0.33 in those samples associated with pAMR 2 vs a median of 0.12 in those samples associated with pAMR 0 or 1. Overall this analysis was limited by sample size and the small number of AMR events (n=4). When examining the relationship in the pediatric samples collected under the plasma-protocol, the relationship between DF and ACR remained robust. There were 32 healthy plasma-protocol pediatric samples associated with 0R biopsies and 13 associated with ACR 1R or higher. Those associated with ACR had a higher DF of 0.62% vs 0.10% in those without ACR (p=0.0006, Figure 4c). ROC using the cutoff value of 0.3, which coincided with the statistically optimized cutoff, revealed an AUC of 0.87, sensitivity of 0.77, specificity of 0.94, and a NPV of 90.9% for the absence of ACR (Figure 4d). Analysis of plasma-protocol DF and pAMR in the pediatric cohort was not performed due to the limited number of pAMR2 samples in this subgroup. Plasma-Protocol Analysis All Rejection (ACR, AMR, CAV): Given the findings above for ACR and AMR, an analysis was undertaken to assess the association of DF and overall allograft health utilizing
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only samples collected under the plasma-protocol. A sample associated with a “healthy” allograft was defined as one that was greater than 7 days post-transplant, associated with no evidence of cellular or humoral rejection (i.e. ACR 0R and pAMR0), nor any evidence of cardiac allograft vasculopathy (CAV score=0) and graft survival for at least 30 days post sample collection (n=38) (Table 1). Samples associated with ACR ≥1R, or pAMR ≥1 were cohorted together as the “rejection” group (n=20). We looked at grade ACR ≥1R or pAMR ≥1 or higher for two reasons: 1) There is evidence to support that ACR 1R and pAMR 1 may represent rejection or an earlier phase of rejection15,16. 2) Biopsies reads are clearly not 100% concordant between pathologists with significant intra and inter reader discordance among pathologists with 71% inter reader concordance reported in Cargo II overall and only 33% concordance in higher grades of rejection17.
When comparing “healthy” vs “rejection” plasma-protocol samples DF was significantly higher in the “rejection” group (0.38% vs 0.10%, p=0.04, Figure 5a). ROC analysis using the cutoff value of 0.3% revealed a sensitivity of 0.60, specificity of 0.92 and a NPV of 81.4% for the absence of any allograft rejection. Using the statistically optimized cutoff of 0.16%, there was some improvement in performance with a sensitivity of 0.75, specificity of 0.79 and a NPV of 85.7% for the absence of any allograft rejection (Figure 5b). Analysis limited to the pediatric plasma-protocol population examining the “healthy” (n=29) vs “rejection” (n=17) groups revealed a similar relationship as in the full population. The DF was higher in the “rejection” group (0.44% vs 0.10%, p=0.002, Figure 5c). ROC analysis using a cutoff value of 0.3, which coincided with the statistically optimized cutoff, revealed an AUC of 0.814 with a sensitivity of 0.65, specificity of 0.93 and a NPV of 81.8% for the absence of any allograft rejection, Figure 5d. Discussion: In this prospective multi-center study examining the relationship between DF and cardiac allograft rejection, a low DF was shown to correlate with a high negative predictive value for rejection on
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EMB. Specifically, two important aspects of the utility of DF as a surveillance tool are elucidated. Firstly, as evidenced by both in vitro studies10 and the data above, cell lysis can adversely affect the utility of DF as a marker for allograft rejection, specifically cellular rejection. Secondly, with careful sample preparation and quality control measures, DF can be highly associated with acute allograft rejection and a clinically useful threshold can be found to distinguish healthy allografts vs those at risk of acute rejection. Furthermore, this study was able to confirm that these associations hold true in not just adults, but also in a pediatric population, arguably a population in whom avoiding multiple routine surveillance biopsies is even more important. While this association has been described previously in small reports, the multicenter nature of this study highlighted the importance of sample preparation for accuracy of a DF assay and demonstrated the ability to overcome this limitation with a clinically feasible protocol. Interestingly, in this study the association of AMR with elevated DF was robust enough to be significant in the entire study population. We hypothesize the observed differences in sensitivities of AMR and ACR detection could be due to more recipient-derived inflammatory leukocytes in ACR which results in higher likelihood of lysis when the plasma protocol is not used. The utility of DF as a screening tool for cardiac allograft health was examined by analyzing samples associated with no graft problems (no rejection, no CAV, healthy recipients) versus those associated with any allograft complication. In this analysis, DF performed well, distinguishing any allograft problem (ACR ≥1R, pAMR ≥1, and/or CAV≥1) with a threshold of 0.3% and a NPV of 80%. DF seems to be exquisitely sensitive for detecting injury to the donor organ. There is no universal consensus on whether or not low-grade rejection (i.e. ACR 1R or pAMR1) requires treatment or even additional surveillance, and many other non-invasive screening tests do not attempt to distinguish ACR 1R or pAMR1 and instead use their values to exclude more severe grades of rejection. In this study DF appears to perform well for higher grade rejection with an NPV greater than 99.7%, however these findings did not reach statistical significance due to the small number of high-grade rejection episodes in the plasma-protocol cohort.
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Limitations: There are limitations to the current study that should be addressed in light of these findings. Due to findings of cell lysis and its effects on DF, the cohort of fully analyzable samples is smaller than anticipated. Despite this, we were able to demonstrate significant associations between DF and allograft rejection, including a strong relationship with AMR in the whole blood-protocol and a strong relationship with ACR in a smaller cohort limited to samples collected under the plasma-protocol although we were limited in our analysis of ACR 2R and higher grades of rejection because of limited numbers. An extension study to the published report is underway with all sample collection performed in accordance with the plasma-protocol and with the goal of validating the cutoff values and findings of the current study. In addition, the current study was limited to local biopsy reads. We have designated an independent group of core pathologists to provide expert re-reads for all biopsies and these will include both the 2006 as well as the historical 1990 ISHLT rejection grading scale. The increased numbers of higher rejection grade as well as the information from both the 2006 and 1990 ISHLT grading scales will allow us to investigate differences in donor fractions among these subtypes. Conclusions: DF is associated with both AMR and ACR in adult and pediatric patients. Sample preparation appears to be critical and the plasma-protocol demonstrates significant apparent advantages over the whole bloodprotocol. Further studies with larger numbers of higher grades of rejection and more clinically associated information are required and are currently underway. Disclosure Statement MEM, ATM, are co-founders of, are board members of, and hold stock options in TAI Diagnostics. PEN is Medical Director of TAI Diagnostics and holds stock options in TAI Diagnostics. SDZ and MH are consultants to and hold stock options in TAI Diagnostics. All remaining authors have no conflicts of interest to disclose.
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This work was funded by a grant from the National Institutes of Health (5R01HL119747) and TAI Diagnostics, Inc through an NIH approved third party agreement. No funding organization had any role in the interpretation or analysis of data and none provided any input or had any right to influence or authorize publication or modification of this manuscript. All analyses, results, conclusions, presentations and publications related to the DTRT study, including all the work contained herein, are reviewed and approved by an independent external oversight committee whose leader reports directly to the MCW Research Conflict of Interest Committee. The members of the oversight committee are professors engaged in their respective specialties at a large academic medical center and include NCF-a physician bioethicist, DLD-a biostatistician, and JSO-a transplant surgeon. We thank these experts and the MCW Research Conflict of Interest Committee for their considerable effort. All analyses, results, conclusions, presentations and publications related to this study are also reviewed and approved by the NIH mandated DTRT steering committee consisting of representative members from all the clinical study sites. We thank the DTRT Aim 1 study coordinators for collecting and shipping thousands of samples and for their tremendous administrative and regulatory support: Columbia University, Jennie McAllister, Andres Gomez; Duke University, Stacey Welsh, Earl Schwarz, Sarah Casalinova; Emory University / Children’s Hospital of Atlanta, Susie Gentry, Raejanna Ashley; Vanderbilt University, Jill Janssen, Cheri Stewart, Norma Suazo Galeano, Karen Trochez; University of Arkansas, Ginger Gilmore, Denise Graves, Grace Goode, Sheila Stroupe; CHW Gail Stendahl, Alyssa Pollow, Jen Yauck; MCW/Froedtert, Sue Mauermann, Katie Vannucchi, Mary Wexler, Sue Cotey, Heidi Martin and Janet Gosset. We also thank the TAI Diagnostics and MCW/CHW study team for running of samples, quality assurance, regulatory support, core support, and data monitoring: Emily Ziegler, Karl Stamm, Amanda Schmidt, Angeles Baker, Kimberly Birmingham, Chris Rosenau, Donna Mahnke, Adam Vepraskas, Michael Wheeler, Brook Fricke, Dianah Kornov, Erin Pederson, Kaitlyn Nielsen, Alfonso Baker, Mary Goestch, Huan ling Liang, Mary Krolikowski, Michell Otto, Alexa Yrineo, and Anne Laulederkind.
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Figure 1. Flowchart of samples
Figure 2. Pairwise analysis adult and pediatric whole blood-protocol AMR
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Figure 3a and 3b. Whole blood-protocol pAMR0/1 vs pAMR2 (adult and pediatric)
Figure 3c and 3d. Whole blood-protocol pAMR0/1 vs pAMR2 (pediatric)
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Figure 4a and b. Adult and pediatric plasma-protocol: ACR = 0R vs. ACR≥1R
Figure 4c and d. Pediatric plasma-protocol: ACR=0R vs. ACR≥1R
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Figure 5a and b. Healthy vs rejection (adult and pediatric plasma-protocol)
Figure 5c and d. Healthy vs rejection (pediatric plasma-protocol)
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Table 1. Inclusions and Exclusions:
Any patient who was “listed” to undergo or had undergone heart transplantation within the past 30 months
Samples within 28 days post treatment for rejection Samples within 7 days post-transplant Samples from women who were pregnant Another solid transplanted organ or bone marrow transplant Any post-transplant lymphoproliferative disease (PTLD) Current cancer or cancer in the previous 2 years Mechanical Circulatory Support at the time of collection
2. Association with EMB
3. Pre-Genotype Quality Control exclusions 4. Post-Genotype Quality Control exclusions
Samples not associated with EMB (samples drawn more than 24 hours before Biopsy or drawn after Biopsy) Temperature, time to spin (Failed for time to spin- more than 5 days), plasma volume, DNA yield
Bioinformatic and sample quality QC
Exclusions for healthy controls
Samples within 30 days of death Samples within 30 days of cardiac arrest (±30 days) Samples during Mechanical Circulatory Support Samples associated to CAV Samples within 14 days of treatment for infection initiation
Samples within 30 days pre to 30 days post of treatment for rejection
Inclusion criteria
Exclusion criteria 1. Clinical exclusions
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Table 2. Demographics
Total Population N=241
Final Population for analysis N=174
Age (years) Mean (SD) Median (Q1-Q3) Range (Min-Max)
23.7 (23.6) 14.7 (3.4-50.6) 0.02-73.4
25.2 (23.5) 16.0 (4.5-51.1) 0.2-73.4
Age Group N (%) Pediatric Adult
146 (60.6) 95 (39.4)
101 (58.0) 73 (42.0)
Gender N (%) Male Female
148 (61.4) 93 (38.6)
110 (63.2) 64 (36.8)
Ethnicity N (%) Hispanic Non-Hispanic Unknown
26 (10.8) 196 (81.3) 19 (7.9)
17 (9.8) 141 (81.0) 16 (9.2)
Race N (%) Asian AA White Unknown
8 (3.3) 56 (23.2) 158 (65.6) 19 (7.9)
5 (2.9) 41 (23.6) 116 (66.7) 12 (6.9)
2537 216 (8.5%) 2321 (91.5%)
624 60 (9.6%) 564 (90.4%)
Total # samples Plasma Whole Blood
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Donor Fraction Cell-Free DNA and Rejection in Adult and Pediatric Heart Transplantation Marc E Richmond MD, MS , Steven D Zangwill MD , Steven J Kindel MD , Shriprasad R Deshpande MBBS, MS , Jacob N Schroder MD , David P Bichell MD , Kenneth R Knecht MD , William T Mahle MD , Mark A Wigger MD , Nunzio A Gaglianello MD , Elfriede Pahl MD , Pippa M Simpson PhD , Mahua Dasgupta MS , Paula E North MD, PhD , Mats Hidestrand PhD , Aoy Tomita-Mitchell PhD , Michael E Mitchell MD PII: DOI: Reference:
S1053-2498(19)31767-X https://doi.org/10.1016/j.healun.2019.11.015 HEALUN 7044
To appear in:
Journal of Heart and Lung Transplantation
Please cite this article as: Marc E Richmond MD, MS , Steven D Zangwill MD , Steven J Kindel MD , Shriprasad R Deshpande MBBS, MS , Jacob N Schroder MD , David P Bichell MD , Kenneth R Knecht MD , William T Mahle MD , Mark A Wigger MD , Nunzio A Gaglianello MD , Elfriede Pahl MD , Pippa M Simpson PhD , Mahua Dasgupta MS , Paula E North MD, PhD , Mats Hidestrand PhD , Aoy Tomita-Mitchell PhD , Michael E Mitchell MD , Donor Fraction CellFree DNA and Rejection in Adult and Pediatric Heart Transplantation, Journal of Heart and Lung Transplantation (2019), doi: https://doi.org/10.1016/j.healun.2019.11.015
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © Published by Elsevier Inc. on behalf of International Society for Heart and Lung Transplantation.
Donor Fraction Cell-Free DNA and Rejection in Adult and Pediatric Heart Transplantation
-Marc E Richmond MD, MS, Department of Pediatrics, Division of Pediatric Cardiology, College of Physicians and Surgeons, Columbia University, New York, NY -Steven D Zangwill MD, Division of Cardiology, Phoenix Children’s Hospital, University of Arizona College of Medicine, Phoenix AZ -Steven J Kindel MD, Division of Pediatric Cardiology, Department of Pediatrics, Medical College of Wisconsin, Herma Heart Institute, Children’s Hospital of Wisconsin, Milwaukee WI -Shriprasad R Deshpande MBBS, MS, Division of Cardiology and Division of Cardiac Intensive Care, Children’s National Hospital, Washington DC -Jacob N Schroder MD, Division of Cardiovascular and Thoracic Surgery, Department of Surgery, Duke University, Durham NC -David P Bichell MD, Division of Pediatric Cardiac Surgery, Department of Surgery, Vanderbilt University, Nashville TN -Kenneth R Knecht MD, Department of Pediatrics, Arkansas Children’s Hospital Little Rock AR -William T Mahle MD, Division of Cardiology, Department of Pediatrics, Emory University, Children’s Healthcare of Atlanta, Atlanta GA -Mark A Wigger MD, Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University, Nashville TN -Nunzio A Gaglianello MD, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI -Elfriede Pahl MD, Division of Cardiology, Department of Pediatrics, Ann & Robert H. Lurie Children’s Hospital Chicago, Chicago, IL
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-Pippa M Simpson PhD, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI -Mahua Dasgupta MS, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI -Paula E North MD, PhD, Department of Pathology, Medical College of Wisconsin, Children’s Hospital of Wisconsin, Milwaukee, WI -Mats Hidestrand PhD, Department of Surgery, Medical College of Wisconsin, WI -Aoy Tomita-Mitchell PhD, Division of Pediatric Cardiothoracic Surgery, Department of Surgery, Medical College of Wisconsin, Herma Heart Institute, Milwaukee, WI -Michael E Mitchell MD, Division of Pediatric Cardiothoracic Surgery, Department of Surgery, Medical College of Wisconsin, Herma Heart Institute, Children’s Hospital of Wisconsin, Milwaukee WI Corresponding Author: Michael E. Mitchell, Herma Heart Institute, Medical College of Wisconsin, Children’s Hospital of Wisconsin, 9000 West Wisconsin Avenue, Milwaukee, WI 53226. Telephone: 414-266-2491, Fax: 414-266-2075. Reprint Requests: Michael E. Mitchell, Herma Heart Institute, Medical College of Wisconsin, Children’s Hospital of Wisconsin, 9000 West Wisconsin Avenue, Milwaukee, Wisconsin, 53226. Telephone: 414266-2491, Fax: 414-266-2075. Email address: [email protected] Keywords: Rejection, Non-invasive detection, Cell-free DNA, Heart transplantation, Pediatric heart transplantation Abstract Word Count: 248 Manuscript Word Count: 3402 Abstract:
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Purpose: Endomyocardial biopsy (EMB) is the current standard for rejection surveillance in heart transplant recipients. Quantification of donor-specific cell-free DNA (cfDNA) may be an appropriate biomarker for non-invasive rejection surveillance. A multi-center prospective blinded study (DNA-based Transplant Rejection Test, DTRT) investigated the value of donor fraction (DF), defined as the ratio of cfDNA specific to the transplanted organ to total amount of cfDNA present in a blood sample. Methods: 241 heart transplant patients were recruited from seven centers. Age at transplant ranged from 8 days to 73 years, with 146 subjects <18 years and 95 ≥ 18 years. All patients were followed for at least one year, with blood samples drawn at routine and for-cause biopsies. 624 biopsy-paired samples were included for analysis via a commercially available cfDNA assay (myTAIHEART®, TAI Diagnostics, Inc). Blinded analysis of repeated measures compared outcomes using receiver operating characteristic (ROC) curves. All primary clinical endpoints were monitored at 100%. All analysis and conclusions were reviewed by both an independent external oversight committee and the NIH mandated DTRT steering committee. Results: DF in ACR 1R/2R (n=15) was higher than ACR 0R (n=42) (p=0.02); DF in pAMR1 (n=8) and pAMR2 (n=12) (p=0.05) were higher than pAMR0 (n=466) (p=0.04 and p=0.05 respectively). By ROC analysis an optimal DF threshold was determined which ruled out the presence of either ACR or AMR. Conclusion: Cell-free DNA donor fraction holds promise as a non-invasive diagnostic test to rule out acute rejection in both adult and pediatric heart transplant populations.
Background: Despite the overall success of heart transplantation as a definitive treatment for end stage heart failure in adults and children, acute allograft rejection remains a major cause of morbidity and mortality. The use of non-invasive surveillance methods for rejection has been of interest to the heart transplant community since the first transplant in 1967. However, no non-invasive test has yet replaced
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endomyocardial biopsy (EMB) as the first line in rejection surveillance. In several recent studies, levels of donor-specific cell-free DNA (cfDNA) in the blood of patients who are experiencing allograft rejection have been shown to correlate with rejection1-3. Our group has previously described the relationship of the ratio of donor-specific cfDNA to total cfDNA, or donor fraction (DF), to acute cellular rejection (ACR) in a pilot study of 158 samples from 88 subjects at a single center3. The current study was designed as a large prospective multi-center observational study of both adult and pediatric heart transplant recipients examining in more detail the assessment of DF cfDNA post-transplant and its utility in predicting graft health. This report focuses on the association between elevated DF and the presence of EMB-confirmed allograft rejection. Methods: A prospective observational study (DNA-Based Transplant Rejection Test (DTRT)) was conducted among seven established heart transplant centers; each obtaining local Institutional Review Board (CHW 10/83, GC 111, CTSI 906) approval. Informed consent was obtained from all subjects prior to onset of study activities transplantation for this minimal risk study. Inclusion and exclusion criteria are listed in Table 1. Clinical information collected included patient demographics and clinical data throughout the admission for transplant, around treatment episodes for rejection, around all symptomatic and asymptomatic biopsies, and around all hospital readmissions. Date and exact time of EMB were checked against blood sample date and time to ensure that all analyzed blood samples were taken prior to any intra-cardiac access, as we have shown that the local trauma of biopsy leads to an acute elevation of cfDNA DF4. Local reads for EMB, hemodynamics at catheterization, echocardiograms, and coronary angiography performed for clinical purposes during the study period were recorded. Dates and times of all critical clinical events were recorded. If a subject was diagnosed with cancer or post-transplant lymphoproliferative disease, or became pregnant, the first dates of diagnosis were recorded, and they were excluded from analysis as these conditions introduce a confounding source of additional “non-self”
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cfDNA (Figure 1 and Table 1). The pathology reports of all biopsies were reviewed and 2004 ISHLT grade was recorded, with biopsy-proven acute cellular rejection (ACR) defined as Grade 1R or higher and biopsy-proven antibody-mediated rejection (AMR) defined as pAMR1 or higher. Results of all coronary angiography during the study period were recorded and graded according to the 2010 ISHLT grading system5 with a cardiac allograft vasculopathy (CAV) grade 1 or higher being defined as the presence of CAV5. Blood sample collection and shipping: Blood samples were obtained from heart transplant recipients in the following clinical scenarios: prior to transplant, days 1, 4, and 7 following transplant, and at discharge from transplant hospitalization; within 24 hours prior to cardiac catheterization; within 24 hours prior to and then days 1, 4, 7, 14, and 28 after initiation of treatment for rejection; at hospital readmission and again prior to discharge if the patient had been treated for either infection or rejection during the readmission. Initially, all patient blood samples for circulating cfDNA determination were collected as whole blood with a typical collection protocol6-9 in 10 ml Cell-Free DNA Blood Collection Tubes (BCT) (Streck, Omaha, NE) herein termed “whole blood-protocol” and immediately coded, de-identified, and delivered within 0-5 days to the CAP and CLIA accredited Children’s Research Institute (CRI) Nucleic Acid Extraction Laboratory (Milwaukee, WI), for plasma isolation and storage prior to cfDNA extraction. Shipping of these samples was accomplished by overnight delivery. Samples were packaged inside a protective pouch with a MicroDL logger (Marathon, San Leandro, CA) to record temperature every five minutes during shipment. The pouch was placed inside an insulated box packed with gel packs properly primed for the seasonal conditions to maintain ambient temperature throughout shipment. As the study commenced an issue was noted with shipment of whole blood specimens: preextraction lysis of leukocytes was occurring despite the presence of a cell membrane stabilizing agent in the collection tube. Enough genomic leukocyte DNA could be released to dilute the DF. To address this, the sample processing protocol was modified to require blood sample centrifugation to separate plasma
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rapidly at the local site of collection, herein termed “plasma-protocol”. Isolated plasma was frozen and then shipped on dry ice to the CRI extraction facility for subsequent cfDNA extraction prior to DF determination at the CAP and CLIA accredited TAI Diagnostics Clinical Reference Laboratory (Wauwatosa, WI). A novel quality assurance protocol based on cfDNA fragmentation analysis was developed to detect problematic post-collection leukocyte lysis so that any samples with evidence of leukocyte lysis above a conservative cut-off level could be rejected from the study in an unbiased manner10. Plasma processing and DNA extraction: Extraction of cfDNA from plasma collected from either the whole blood-protocol or plasma-protocol was performed using a ReliaPrepTM HT Circulating Nucleic Acid Kit, Custom (Promega, Madison, WI)10. Recipient and donor genomic DNA from buffy coats prepared from these samples were extracted by using ReliaPrepTM Large Volume gDNA Isolation System (Promega)10. Donor genomic DNA from tissue was extracted by using QIAamp DNA Micro Kit (Qiagen, Germantown, MD)10. Total cfDNA analysis: Total cfDNA (TCF) concentration of the plasma samples, including those collected under both whole blood and plasma protocols were measured by quantitative real-time PCR9. DF Analysis: Donor-specific cfDNA is calculated as a fraction (DF) of the total cfDNA and is performed without the requirement of a donor sample (myTAIHEART)3,10. The test quantitatively genotypes (qGT) a panel of 94 high frequency SNPs selected for their ability to reliably discriminate between alleles offering a rapid, non-invasive, high-throughput, and cost-effective manner to determine donor-specific cfDNA in the clinical transplant setting10. Briefly, sample cfDNA (15 ng) is spiked with an exogenous internal control and amplified by high-fidelity PCR as a multiplexed library followed by qGT10. In addition, recipient genomic DNA is extracted from leukocytes from a separate whole blood sample and analyzed with a “basic genotyping” (bGT) algorithm10.
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Clinical Data Collection: Clinical, laboratory, cardiac catheterization and echocardiographic data were recorded and data were managed using Research Electronic Data Capture (REDCap) tools hosted at the Medical College of Wisconsin (MCW, Milwaukee, WI)11. Monitoring: A risk-based approach was utilized to monitor the extensive database including one hundred percent monitoring of data fields required for the analysis of primary endpoints and spot monitoring of other data fields. Statistical Methods: Median DF cfDNA levels and interquartile ranges (IQR) are reported. To take account of the repeated measures, a generalized estimating equation model was used12,13. Generalized estimating equation (GEE) allowed for repeated measures12,13 in comparing across the rejection grades and performing ROC analysis. Subjects as clusters with logit link function and an autoregressive covariance structure was used. Due to the small sample size an unadjusted p value <0.05 was reported as significant. ROC curves were examined to assess the sensitivity and specificity of DF to compare its ability to distinguish healthy 0R vs 1R/2R14. A threshold value was chosen that maximized the sensitivity while allowing for reasonable specificity. Results were compiled for the whole blood-protocol, the plasmaprotocol, and for both collection protocols combined, with a sub analysis of pediatric subjects. Results: A total of 2537 samples were obtained during the study from 241 consented and transplanted individual subjects. For the specific purposes of this analysis with an aim to describe the relationship between DF and rejection as determined by EMB, ultimately 624 samples from 174 subjects were included after exclusions were applied (Figure 1). Clinical exclusions eliminated 970 samples and of those 1567 remaining, 429 were further excluded as they were not associated with EMB. This left a total of 1138 samples from 203 individual subjects. Before genotyping, 502 samples were excluded because of predefined quality control exclusions (Table 1, point 3). After genotyping but before unblinded
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analysis 12 samples were excluded for bioinformatic and sample quality QC (Table 1, point 4). This left 624 EMB associated samples from 174 individuals and formed the cohort for blinded analysis. Within the analytic cohort, 564 samples were drawn under the whole blood-protocol and 60 were collected using the plasma-protocol. Subject Demographics: Given the combined pediatric and adult subject group, the age at transplant of the 241 consented and transplanted subjects was 14.7 (3.4-50.6) years, with the youngest subject age 8 days at the time of transplant and the oldest 73.4 years. Pediatric patients (<18 years) comprised 60.0% of the total patient population (n=146). The population was mostly male (61.4 %), and the majority were of white race (65.6%), with 23.2% of subjects’ race reported as Black or African American. 10.8% of subjects reported Hispanic or Latino ethnicity. After exclusion criteria were applied to the sample and subject population, the final population demographics changed slightly with respect to age at transplant 16 (4.5-51.1) years, with a range of 56 days to 73.4 years. There were 101 (58%) pediatric patients (<18 years). The population for analysis remained predominantly male (63.2%) and white (66.7%), with 23.6% identifying as Black race and 9.8% of Hispanic or Latino ethnicity (Table 2). Whole Blood Protocol Analysis: Using samples collected under the whole blood-protocol we examined the relationship between DF and the presence of ACR. A total of 533 EMB associated samples were collected using the whole blood-protocol and included 357 with ACR 0R (healthy), 155 with ACR 1R and 21 with ACR 2R. In this analysis there was no difference in DF amongst the three groups (0.11% vs 0.12% vs 0.14%), nor was there a difference in DF between grade 0R and a composite group consisting of all samples associated with grade 1R or higher 0.11% vs 0.12%, p=0.56). Furthermore, ROC analysis revealed an AUC of only 0.525 in the whole blood group. We then sought to examine the relationship between DF and the presence of AMR using samples collected under the whole blood-protocol. A total of 466 samples were associated with biopsy read of
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pAMR0, with 8 showing pAMR1 (either pAMR1-i or pAMR 1-h) and 12 with pAMR2. In pairwise analysis of samples collected under the whole blood-protocol (Figure 2), there were significant differences in DF between the pAMR0 group and pAMR1 (p=0.04), as well as between pAMR0 and pAMR2 (p=0.05), however there was no statistical difference between pAMR1 and pAMR2 groups with respect to DF values (0.21% vs 0.30%, p=0.35). Since pAMR1 is a heterogeneous group consisting of both biopsies with evidence of immunohistochemical staining only (pAMR1i) as well as those with cellular edema without evidence of complement deposition (pAMR1h), the decision was made to treat pAMR2 as evidence of definitive acute antibody-mediated rejection. As such, when comparing samples from the whole blood protocol associated with pAMR2 vs those with healthy pAMR0 or pAMR1, pAMR2 was associated with a higher DF (0.30% vs 0.11%, p=0.04, Figure 3a). Using the predefined cutoff value of 0.3%, ROC analysis resulted in a sensitivity of 0.50 and a specificity of 0.88. Using the statistically optimized cutoff value of 0.19% resulted in improved performance; with a sensitivity of 0.92 and specificity of 0.75, yielding a NPV of 99.7% for the absence of pAMR2 or higher (Figure 3b). When further examining this relationship in the pediatric whole blood-protocol population only, 200 samples were associated with CR0 and 58 samples were associated with CR1/2. There was no significant difference between groups (p=0.71), and ROC analysis resulted in an AUC of 0.53, sensitivity of 0.76, specificity of 0.36, at a cutoff of 0.1. With respect to AMR in the pediatric whole blood-protocol population only, 239 healthy samples were associated with pAMR0 or pAMR1 while 11 samples were associated with pAMR2. There was a marginal difference in the DF between these groups with 0.13% in the pAMR0/1 group and 0.31% in the pAMR2 group (p=0.09, Figure 3c). ROC analysis with the same cutoff value of 0.19 determined from the full study population resulted in an AUC of 0.84, sensitivity of 1, specificity of 0.67 and a NPV of 100% for the absence of pAMR2 or higher (Figure 3d).
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Plasma Protocol Analysis: Concerned that the phenomenon of cell lysis was diluting the DF signal and impacting the ability to detect differences between samples with and without rejection, and more specifically ACR, the population of samples collected using the plasma-protocol were analyzed. Forty-two healthy plasma-protocol samples were associated with no cellular rejection (Grade 0R) and 15 were associated with ACR 1R or higher (14 grade 1R, 1 grade 2R). There was a significant difference in the DF between those samples associated with grade 1R or higher vs those without evidence of ACR (0.49% vs 0.10%, p=0.02, Figure 4a). ROC analysis of this population with a cutoff value of 0.3 resulted in sensitivity of 0.73, specificity of 0.93 and a NPV of 90.7% for the absence of ACR. Performance at the statistically optimized cutoff value of 0.23 was slightly improved with a sensitivity of 0.8, specificity of 0.88 and a NPV of 92.5%, (Figure 4b). Examining the relationship between DF and pAMR in the plasma-protocol samples there was a significant difference in the DF between those samples with pAMR 2 and those with pAMR 0 or 1 with a median DF of 0.33 in those samples associated with pAMR 2 vs a median of 0.12 in those samples associated with pAMR 0 or 1. Overall this analysis was limited by sample size and the small number of AMR events (n=4). When examining the relationship in the pediatric samples collected under the plasma-protocol, the relationship between DF and ACR remained robust. There were 32 healthy plasma-protocol pediatric samples associated with 0R biopsies and 13 associated with ACR 1R or higher. Those associated with ACR had a higher DF of 0.62% vs 0.10% in those without ACR (p=0.0006, Figure 4c). ROC using the cutoff value of 0.3, which coincided with the statistically optimized cutoff, revealed an AUC of 0.87, sensitivity of 0.77, specificity of 0.94, and a NPV of 90.9% for the absence of ACR (Figure 4d). Analysis of plasma-protocol DF and pAMR in the pediatric cohort was not performed due to the limited number of pAMR2 samples in this subgroup. Plasma-Protocol Analysis All Rejection (ACR, AMR, CAV): Given the findings above for ACR and AMR, an analysis was undertaken to assess the association of DF and overall allograft health utilizing
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only samples collected under the plasma-protocol. A sample associated with a “healthy” allograft was defined as one that was greater than 7 days post-transplant, associated with no evidence of cellular or humoral rejection (i.e. ACR 0R and pAMR0), nor any evidence of cardiac allograft vasculopathy (CAV score=0) and graft survival for at least 30 days post sample collection (n=38) (Table 1). Samples associated with ACR ≥1R, or pAMR ≥1 were cohorted together as the “rejection” group (n=20). We looked at grade ACR ≥1R or pAMR ≥1 or higher for two reasons: 1) There is evidence to support that ACR 1R and pAMR 1 may represent rejection or an earlier phase of rejection15,16. 2) Biopsies reads are clearly not 100% concordant between pathologists with significant intra and inter reader discordance among pathologists with 71% inter reader concordance reported in Cargo II overall and only 33% concordance in higher grades of rejection17.
When comparing “healthy” vs “rejection” plasma-protocol samples DF was significantly higher in the “rejection” group (0.38% vs 0.10%, p=0.04, Figure 5a). ROC analysis using the cutoff value of 0.3% revealed a sensitivity of 0.60, specificity of 0.92 and a NPV of 81.4% for the absence of any allograft rejection. Using the statistically optimized cutoff of 0.16%, there was some improvement in performance with a sensitivity of 0.75, specificity of 0.79 and a NPV of 85.7% for the absence of any allograft rejection (Figure 5b). Analysis limited to the pediatric plasma-protocol population examining the “healthy” (n=29) vs “rejection” (n=17) groups revealed a similar relationship as in the full population. The DF was higher in the “rejection” group (0.44% vs 0.10%, p=0.002, Figure 5c). ROC analysis using a cutoff value of 0.3, which coincided with the statistically optimized cutoff, revealed an AUC of 0.814 with a sensitivity of 0.65, specificity of 0.93 and a NPV of 81.8% for the absence of any allograft rejection, Figure 5d. Discussion: In this prospective multi-center study examining the relationship between DF and cardiac allograft rejection, a low DF was shown to correlate with a high negative predictive value for rejection on
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EMB. Specifically, two important aspects of the utility of DF as a surveillance tool are elucidated. Firstly, as evidenced by both in vitro studies10 and the data above, cell lysis can adversely affect the utility of DF as a marker for allograft rejection, specifically cellular rejection. Secondly, with careful sample preparation and quality control measures, DF can be highly associated with acute allograft rejection and a clinically useful threshold can be found to distinguish healthy allografts vs those at risk of acute rejection. Furthermore, this study was able to confirm that these associations hold true in not just adults, but also in a pediatric population, arguably a population in whom avoiding multiple routine surveillance biopsies is even more important. While this association has been described previously in small reports, the multicenter nature of this study highlighted the importance of sample preparation for accuracy of a DF assay and demonstrated the ability to overcome this limitation with a clinically feasible protocol. Interestingly, in this study the association of AMR with elevated DF was robust enough to be significant in the entire study population. We hypothesize the observed differences in sensitivities of AMR and ACR detection could be due to more recipient-derived inflammatory leukocytes in ACR which results in higher likelihood of lysis when the plasma protocol is not used. The utility of DF as a screening tool for cardiac allograft health was examined by analyzing samples associated with no graft problems (no rejection, no CAV, healthy recipients) versus those associated with any allograft complication. In this analysis, DF performed well, distinguishing any allograft problem (ACR ≥1R, pAMR ≥1, and/or CAV≥1) with a threshold of 0.3% and a NPV of 80%. DF seems to be exquisitely sensitive for detecting injury to the donor organ. There is no universal consensus on whether or not low-grade rejection (i.e. ACR 1R or pAMR1) requires treatment or even additional surveillance, and many other non-invasive screening tests do not attempt to distinguish ACR 1R or pAMR1 and instead use their values to exclude more severe grades of rejection. In this study DF appears to perform well for higher grade rejection with an NPV greater than 99.7%, however these findings did not reach statistical significance due to the small number of high-grade rejection episodes in the plasma-protocol cohort.
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Limitations: There are limitations to the current study that should be addressed in light of these findings. Due to findings of cell lysis and its effects on DF, the cohort of fully analyzable samples is smaller than anticipated. Despite this, we were able to demonstrate significant associations between DF and allograft rejection, including a strong relationship with AMR in the whole blood-protocol and a strong relationship with ACR in a smaller cohort limited to samples collected under the plasma-protocol although we were limited in our analysis of ACR 2R and higher grades of rejection because of limited numbers. An extension study to the published report is underway with all sample collection performed in accordance with the plasma-protocol and with the goal of validating the cutoff values and findings of the current study. In addition, the current study was limited to local biopsy reads. We have designated an independent group of core pathologists to provide expert re-reads for all biopsies and these will include both the 2006 as well as the historical 1990 ISHLT rejection grading scale. The increased numbers of higher rejection grade as well as the information from both the 2006 and 1990 ISHLT grading scales will allow us to investigate differences in donor fractions among these subtypes. Conclusions: DF is associated with both AMR and ACR in adult and pediatric patients. Sample preparation appears to be critical and the plasma-protocol demonstrates significant apparent advantages over the whole bloodprotocol. Further studies with larger numbers of higher grades of rejection and more clinically associated information are required and are currently underway. Disclosure Statement MEM, ATM, are co-founders of, are board members of, and hold stock options in TAI Diagnostics. PEN is Medical Director of TAI Diagnostics and holds stock options in TAI Diagnostics. SDZ and MH are consultants to and hold stock options in TAI Diagnostics. All remaining authors have no conflicts of interest to disclose.
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This work was funded by a grant from the National Institutes of Health (5R01HL119747) and TAI Diagnostics, Inc through an NIH approved third party agreement. No funding organization had any role in the interpretation or analysis of data and none provided any input or had any right to influence or authorize publication or modification of this manuscript. All analyses, results, conclusions, presentations and publications related to the DTRT study, including all the work contained herein, are reviewed and approved by an independent external oversight committee whose leader reports directly to the MCW Research Conflict of Interest Committee. The members of the oversight committee are professors engaged in their respective specialties at a large academic medical center and include NCF-a physician bioethicist, DLD-a biostatistician, and JSO-a transplant surgeon. We thank these experts and the MCW Research Conflict of Interest Committee for their considerable effort. All analyses, results, conclusions, presentations and publications related to this study are also reviewed and approved by the NIH mandated DTRT steering committee consisting of representative members from all the clinical study sites. We thank the DTRT Aim 1 study coordinators for collecting and shipping thousands of samples and for their tremendous administrative and regulatory support: Columbia University, Jennie McAllister, Andres Gomez; Duke University, Stacey Welsh, Earl Schwarz, Sarah Casalinova; Emory University / Children’s Hospital of Atlanta, Susie Gentry, Raejanna Ashley; Vanderbilt University, Jill Janssen, Cheri Stewart, Norma Suazo Galeano, Karen Trochez; University of Arkansas, Ginger Gilmore, Denise Graves, Grace Goode, Sheila Stroupe; CHW Gail Stendahl, Alyssa Pollow, Jen Yauck; MCW/Froedtert, Sue Mauermann, Katie Vannucchi, Mary Wexler, Sue Cotey, Heidi Martin and Janet Gosset. We also thank the TAI Diagnostics and MCW/CHW study team for running of samples, quality assurance, regulatory support, core support, and data monitoring: Emily Ziegler, Karl Stamm, Amanda Schmidt, Angeles Baker, Kimberly Birmingham, Chris Rosenau, Donna Mahnke, Adam Vepraskas, Michael Wheeler, Brook Fricke, Dianah Kornov, Erin Pederson, Kaitlyn Nielsen, Alfonso Baker, Mary Goestch, Huan ling Liang, Mary Krolikowski, Michell Otto, Alexa Yrineo, and Anne Laulederkind.
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Figure 1. Flowchart of samples
Figure 2. Pairwise analysis adult and pediatric whole blood-protocol AMR
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Figure 3a and 3b. Whole blood-protocol pAMR0/1 vs pAMR2 (adult and pediatric)
Figure 3c and 3d. Whole blood-protocol pAMR0/1 vs pAMR2 (pediatric)
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Figure 4a and b. Adult and pediatric plasma-protocol: ACR = 0R vs. ACR≥1R
Figure 4c and d. Pediatric plasma-protocol: ACR=0R vs. ACR≥1R
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Figure 5a and b. Healthy vs rejection (adult and pediatric plasma-protocol)
Figure 5c and d. Healthy vs rejection (pediatric plasma-protocol)
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Table 1. Inclusions and Exclusions:
Any patient who was “listed” to undergo or had undergone heart transplantation within the past 30 months
Samples within 28 days post treatment for rejection Samples within 7 days post-transplant Samples from women who were pregnant Another solid transplanted organ or bone marrow transplant Any post-transplant lymphoproliferative disease (PTLD) Current cancer or cancer in the previous 2 years Mechanical Circulatory Support at the time of collection
2. Association with EMB
3. Pre-Genotype Quality Control exclusions 4. Post-Genotype Quality Control exclusions
Samples not associated with EMB (samples drawn more than 24 hours before Biopsy or drawn after Biopsy) Temperature, time to spin (Failed for time to spin- more than 5 days), plasma volume, DNA yield
Bioinformatic and sample quality QC
Exclusions for healthy controls
Samples within 30 days of death Samples within 30 days of cardiac arrest (±30 days) Samples during Mechanical Circulatory Support Samples associated to CAV Samples within 14 days of treatment for infection initiation
Samples within 30 days pre to 30 days post of treatment for rejection
Inclusion criteria
Exclusion criteria 1. Clinical exclusions
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Table 2. Demographics
Total Population N=241
Final Population for analysis N=174
Age (years) Mean (SD) Median (Q1-Q3) Range (Min-Max)
23.7 (23.6) 14.7 (3.4-50.6) 0.02-73.4
25.2 (23.5) 16.0 (4.5-51.1) 0.2-73.4
Age Group N (%) Pediatric Adult
146 (60.6) 95 (39.4)
101 (58.0) 73 (42.0)
Gender N (%) Male Female
148 (61.4) 93 (38.6)
110 (63.2) 64 (36.8)
Ethnicity N (%) Hispanic Non-Hispanic Unknown
26 (10.8) 196 (81.3) 19 (7.9)
17 (9.8) 141 (81.0) 16 (9.2)
Race N (%) Asian AA White Unknown
8 (3.3) 56 (23.2) 158 (65.6) 19 (7.9)
5 (2.9) 41 (23.6) 116 (66.7) 12 (6.9)
2537 216 (8.5%) 2321 (91.5%)
624 60 (9.6%) 564 (90.4%)
Total # samples Plasma Whole Blood
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