Noninvasive detection of graft injury after heart transplant using donor-derived cell-free DNA: A prospective multicenter study.

Standardized donor-derived cell-free DNA (dd-cfDNA) testing has been introduced into clinical use to monitor kidney transplant recipients for rejection. This report describes the performance of this dd-cfDNA assay to detect allograft rejection in samples from heart transplant (HT) recipients undergoing surveillance monitoring across the United States. Venous blood was longitudinally sampled from 740 HT recipients from 26 centers and in a single-center cohort of 33 patients at high risk for antibody-mediated rejection (AMR). Plasma dd-cfDNA was quantified by using targeted amplification and sequencing of a single nucleotide polymorphism panel. The dd-cfDNA levels were correlated to paired events of biopsy-based diagnosis of rejection. The median dd-cfDNA was 0.07% in reference HT recipients (2164 samples) and 0.17% in samples classified as acute rejection (35 samples; P = .005). At a 0.2% threshold, dd-cfDNA had a 44% sensitivity to detect rejection and a 97% negative predictive value. In the cohort at risk for AMR (11 samples), dd-cfDNA levels were elevated 3-fold in AMR compared with patients without AMR (99 samples, P = .004). The standardized dd-cfDNA test identified acute rejection in samples from a broad population of HT recipients. The reported test performance characteristics will guide the next stage of clinical utility studies of the dd-cfDNA assay.

Cell-Free DNA and Active Rejection in Kidney Allografts.

Histologic analysis of the allograft biopsy specimen is the standard method used to differentiate rejection from other injury in kidney transplants. Donor-derived cell-free DNA (dd-cfDNA) is a noninvasive test of allograft injury that may enable more frequent, quantitative, and safer assessment of allograft rejection and injury status. To investigate this possibility, we prospectively collected blood specimens at scheduled intervals and at the time of clinically indicated biopsies. In 102 kidney recipients, we measured plasma levels of dd-cfDNA and correlated the levels with allograft rejection status ascertained by histology in 107 biopsy specimens. The dd-cfDNA level discriminated between biopsy specimens showing any rejection (T cell-mediated rejection or antibody-mediated rejection [ABMR]) and controls (no rejection histologically), P<0.001 (receiver operating characteristic area under the curve [AUC], 0.74; 95% confidence interval [95% CI], 0.61 to 0.86). Positive and negative predictive values for active rejection at a cutoff of 1.0% dd-cfDNA were 61% and 84%, respectively. The AUC for discriminating ABMR from samples without ABMR was 0.87 (95% CI, 0.75 to 0.97). Positive and negative predictive values for ABMR at a cutoff of 1.0% dd-cfDNA were 44% and 96%, respectively. Median dd-cfDNA was 2.9% (ABMR), 1.2% (T cell-mediated types ≥IB), 0.2% (T cell-mediated type IA), and 0.3% in controls (P=0.05 for T cell-mediated rejection types ≥IB versus controls). Thus, dd-cfDNA may be used to assess allograft rejection and injury; dd-cfDNA levels <1% reflect the absence of active rejection (T cell-mediated type ≥IB or ABMR) and levels >1% indicate a probability of active rejection.

Clinical usefulness of gene-expression profile to rule out acute rejection after heart transplantation: CARGO II.

AIMS: A non-invasive gene-expression profiling (GEP) test for rejection surveillance of heart transplant recipients originated in the USA. A European-based study, Cardiac Allograft Rejection Gene Expression Observational II Study (CARGO II), was conducted to further clinically validate the GEP test performance. METHODS AND RESULTS: Blood samples for GEP testing (AlloMap(®), CareDx, Brisbane, CA, USA) were collected during post-transplant surveillance. The reference standard for rejection status was based on histopathology grading of tissue from endomyocardial biopsy. The area under the receiver operating characteristic curve (AUC-ROC), negative (NPVs), and positive predictive values (PPVs) for the GEP scores (range 0-39) were computed. Considering the GEP score of 34 as a cut-off (>6 months post-transplantation), 95.5% (381/399) of GEP tests were true negatives, 4.5% (18/399) were false negatives, 10.2% (6/59) were true positives, and 89.8% (53/59) were false positives. Based on 938 paired biopsies, the GEP test score AUC-ROC for distinguishing ≥3A rejection was 0.70 and 0.69 for ≥2-6 and >6 months post-transplantation, respectively. Depending on the chosen threshold score, the NPV and PPV range from 98.1 to 100% and 2.0 to 4.7%, respectively. CONCLUSION: For ≥2-6 and >6 months post-transplantation, CARGO II GEP score performance (AUC-ROC = 0.70 and 0.69) is similar to the CARGO study results (AUC-ROC = 0.71 and 0.67). The low prevalence of ACR contributes to the high NPV and limited PPV of GEP testing. The choice of threshold score for practical use of GEP testing should consider overall clinical assessment of the patient's baseline risk for rejection.

Performance of gene-expression profiling test score variability to predict future clinical events in heart transplant recipients.

BACKGROUND: A single non-invasive gene expression profiling (GEP) test (AlloMap®) is often used to discriminate if a heart transplant recipient is at a low risk of acute cellular rejection at time of testing. In a randomized trial, use of the test (a GEP score from 0-40) has been shown to be non-inferior to a routine endomyocardial biopsy for surveillance after heart transplantation in selected low-risk patients with respect to clinical outcomes. Recently, it was suggested that the within-patient variability of consecutive GEP scores may be used to independently predict future clinical events; however, future studies were recommended. Here we performed an analysis of an independent patient population to determine the prognostic utility of within-patient variability of GEP scores in predicting future clinical events. METHODS: We defined the GEP score variability as the standard deviation of four GEP scores collected ≥315 days post-transplantation. Of the 737 patients from the Cardiac Allograft Rejection Gene Expression Observational (CARGO) II trial, 36 were assigned to the composite event group (death, re-transplantation or graft failure ≥315 days post-transplantation and within 3 years of the final GEP test) and 55 were assigned to the control group (non-event patients). In this case-controlled study, the performance of GEP score variability to predict future events was evaluated by the area under the receiver operator characteristics curve (AUC ROC). The negative predictive values (NPV) and positive predictive values (PPV) including 95 % confidence intervals (CI) of GEP score variability were calculated. RESULTS: The estimated prevalence of events was 17 %. Events occurred at a median of 391 (inter-quartile range 376) days after the final GEP test. The GEP variability AUC ROC for the prediction of a composite event was 0.72 (95 % CI 0.6-0.8). The NPV for GEP score variability of 0.6 was 97 % (95 % CI 91.4-100.0); the PPV for GEP score variability of 1.5 was 35.4 % (95 % CI 13.5-75.8). CONCLUSION: In heart transplant recipients, a GEP score variability may be used to predict the probability that a composite event will occur within 3 years after the last GEP score. TRIAL REGISTRATION: Clinicaltrials.gov identifier NCT00761787.

Gene-expression profiling for rejection surveillance after cardiac transplantation.

BACKGROUND: Endomyocardial biopsy is the standard method of monitoring for rejection in recipients of a cardiac transplant. However, this procedure is uncomfortable, and there are risks associated with it. Gene-expression profiling of peripheral-blood specimens has been shown to correlate with the results of an endomyocardial biopsy. METHODS: We randomly assigned 602 patients who had undergone cardiac transplantation 6 months to 5 years previously to be monitored for rejection with the use of gene-expression profiling or with the use of routine endomyocardial biopsies, in addition to clinical and echocardiographic assessment of graft function. We performed a noninferiority comparison of the two approaches with respect to the composite primary outcome of rejection with hemodynamic compromise, graft dysfunction due to other causes, death, or retransplantation. RESULTS: During a median follow-up period of 19 months, patients who were monitored with gene-expression profiling and those who underwent routine biopsies had similar 2-year cumulative rates of the composite primary outcome (14.5% and 15.3%, respectively; hazard ratio with gene-expression profiling, 1.04; 95% confidence interval, 0.67 to 1.68). The 2-year rates of death from any cause were also similar in the two groups (6.3% and 5.5%, respectively; P=0.82). Patients who were monitored with the use of gene-expression profiling underwent fewer biopsies per person-year of follow-up than did patients who were monitored with the use of endomyocardial biopsies (0.5 vs. 3.0, P<0.001). CONCLUSIONS: Among selected patients who had received a cardiac transplant more than 6 months previously and who were at a low risk for rejection, a strategy of monitoring for rejection that involved gene-expression profiling, as compared with routine biopsies, was not associated with an increased risk of serious adverse outcomes and resulted in the performance of significantly fewer biopsies. (ClinicalTrials.gov number, NCT00351559.)

Infectious complications after heart transplantation in patients screened with gene expression profiling.

BACKGROUND: The risk of infection after heart transplantation is highest within the first year and represents the leading cause of early mortality. In this cohort of patients enrolled in the Outcomes AlloMap Registry (OAR), we sought to describe infection episodes (IEp) resulting in hospitalization, in the early (<1 year) and late (≥1 year) post-transplant period and determine the impact of immunosuppression on incidence of infection. METHODS: The primary aim was to assess the incidence and nature of IEp. The secondary aim was to evaluate the effect of potential risk factors, such as recipient age; sex; body mass index; panel-reactive antibodies; cytomegalovirus (CMV) primary mismatch; prednisone, tacrolimus, and sirolimus levels; and gene expression profile (GEP) score, in the development of IEp. RESULTS: The OAR comprises 1,504 patients, of whom 220 patients (14.6%) had an IEp during a median follow-up period of 382 days (interquartile range [IQR] 230 to 579 days). The cause-specific 5-year hazard ratio for any infection was 2.029 (p = 0.12). The pattern of early infection was consistent with nosocomial and opportunistic causes, whereas later infection was consistent with late-onset opportunistic and community-acquired etiologies. Sixty-two percent of the infections occurred early. In the time-dependent analysis, higher prednisone dose (log prednisone, hazard ratio [HR] 1.30, p = 0.022) was the most significant risk factor for all IEp. CONCLUSIONS: In the OAR cohort, the majority of infections occurred within 1 year after transplantation. Clinicians may consider more aggressive prednisone withdrawal in low-risk patients to reduce IEp.

Risk evaluation using gene expression screening to monitor for acute cellular rejection in heart transplant recipients.

BACKGROUND: Gene expression profiling (GEP) was developed for non-invasive surveillance of acute cellular rejection. Despite its widespread use, there has been a paucity in outcome data for patients managed with GEP outside of clinical trials. METHODS: The Outcomes AlloMap Registry (OAR) is an observational, prospective, multicenter study including patients aged ≥ 15 years and ≥ 55 days post-cardiac transplant. Primary outcome was death and a composite outcome of hemodynamically significant rejection, graft dysfunction, retransplantation, or death. Secondary outcomes included readmission rates and development of coronary allograft vasculopathy and malignancies. RESULTS: The study included 1,504 patients, who were predominantly Caucasian (69%), male (74%), and aged 54.1 ± 12.9 years. The prevalence of moderate to severe acute cellular rejection (≥2R) was 2.0% from 2 to 6 months and 2.2% after 6 months. In the OAR there was no association between higher GEP scores and coronary allograft vasculopathy (p = 0.25), cancer (p = 0.16), or non-cytomegalovirus infection (p = 0.10). Survival at 1, 2, and 5 years post-transplant was 99%, 98%, and 94%, respectively. The composite outcome occurred in 103 patients during the follow-up period. GEP scores in dual-organ recipients (heart-kidney and heart-liver) were comparable to heart-alone recipients. CONCLUSIONS: This registry comprises the largest contemporary cohort of patients undergoing GEP for surveillance. Among patients selected for GEP surveillance, survival is excellent, and rates of acute rejection, graft dysfunction, readmission, and death are low.

Gene expression profiling and racial disparities in outcomes after heart transplantation.

BACKGROUND: African Americans (AAs) have lower survival rates after heart transplantation (HTx) than Caucasians. The aim of this analysis was to evaluate racial differences in gene expression and their associations with survival and the composite outcome of death, retransplant, rejection with hemodynamic compromise, and graft dysfunction in the Outcomes AlloMap Registry. METHODS: Registry participants included low-risk Caucasian and AA heart transplant recipients with a baseline and at least 1 follow-up gene expression test (AlloMap(C)) within the first year after HTx. The Kaplan-Meier method with delayed entry was used to describe differences in outcomes. Multivariable Cox hazard regression was used to evaluate the associations of overall gene expression profiling score, MARCH8 and FLT3 expression, and tacrolimus levels with each outcome, and stratified Cox models were developed to quantify race-specific associations. RESULTS: Among 933 eligible recipients, 737 (79%) were Caucasian and 196 (21%) were AA. Compared with Caucasians, AAs were significantly younger (55 vs 59 years, p < 0.001), with higher rates of non-ischemic cardiomyopathy (68% vs 50%, p < 0.001), sensitization (>10% panel reactive antibody, 16% vs 9.1%, p = 0.009), and human leukocyte antigen mismatches (7 vs 7, p = 0.01), but less frequent primary cytomegalovirus serostatus mismatch (14.31% vs 27.3%, p < 0.001). Overall, AAs had an increased adjusted mortality risk (hazard ratio [HR] 4.13, p = 0.007). Higher tacrolimus levels were associated with decreased mortality in AAs (HR 0.62, p = 0.009). Overall gene expression profiling score was associated with increased mortality among Caucasians (HR 1.21, p = 0.048). In Caucasians, but not AAs, overexpression of MARCH8 was associated with increased mortality (HR 2.90, p = 0.001). FLT3 upregulation was associated with increased mortality (HR 2.42, p = 0.033) in AAs. There was an inverse relationship between FLT3 expression and tacrolimus levels (-0.029 and -0.176, respectively) in Caucasians and AAs. CONCLUSIONS: AAs have a significantly higher mortality risk after HTx than Caucasians, even in the low-risk Outcomes AlloMap Registry population. AAs and Caucasians had differential outcomes based upon the varying expression of MARCH8 and FLT3 genes following HTx.

Donor-derived Cell-free DNA Identifies Antibody-mediated Rejection in Donor Specific Antibody Positive Kidney Transplant Recipients.

BACKGROUND: Elevated levels of donor-derived cell-free DNA (dd-cfDNA) in the plasma of renal allograft recipients indicates organ injury and an increased probability of active rejection. Donor-specific antibodies (DSA) to HLA antigens are associated with risk of antibody-mediated rejection (ABMR). This study assessed the combined use of dd-cfDNA and DSA testing to diagnose active ABMR. METHODS: Donor-derived cell-free DNA was assayed in 90 blood samples with paired DSA and clinically indicated biopsies from 87 kidney transplant patients. Sixteen cases met criteria for active ABMR. Performance characteristics of dd-cfDNA for diagnosis of active ABMR were determined for samples with prior or current positive DSA (DSA+, n = 33). RESULTS: The median level of dd-cfDNA (2.9%) in DSA+ patients with active ABMR was significantly higher than the median level (0.34%) in DSA+ patients without ABMR (P < 0.001). The median level of dd-cfDNA in DSA- patients was 0.29%. The positive predictive value of dd-cfDNA (at 1%) to detect active ABMR in DSA+ patients was 81%, whereas the negative predictive value was 83%. The positive predictive value for DSA+ alone was 48%. CONCLUSIONS: The combined use of dd-cfDNA and DSA testing may improve the noninvasive diagnosis of active ABMR in kidney transplant patients. Patients with dd-cfDNA+/ DSA+ results have a high probability of active ABMR.

Biological Variation of Donor-Derived Cell-Free DNA in Renal Transplant Recipients: Clinical Implications.

BACKGROUND: Previous studies have demonstrated that donor-derived cell-free DNA (dd-cfDNA) found in circulating blood of transplant recipients may serve as a noninvasive biomarker of allograft rejection. To better interpret the clinical meaning of dd-cfDNA, it is essential to understand the biological variation of this biomarker in stable healthy recipients. This report establishes the biological variation and clinical reference intervals of dd-cfDNA in renal transplant recipients by using an analytically validated assay that has a CV of 6.8%. METHODS: We sampled venous blood at patient surveillance visits (typically at posttransplant months 1-4, 6, 9, and 12) in a 14-center observational study. Patients with stable renal allograft function spanning ≥3 serial visits were selected. We used AlloSure®, a targeted next-generation sequencing-based approach, to measure dd-cfDNA in the plasma and computed the intraindividual CV (CVI) and interindividual CV (CVG), the index of individuality (II), and reference change value (RCV). RESULTS: Of 93 patients, 61% were men, 56% were Caucasian, mean age was 49 years, and 63% were deceased donor kidney recipients. Of 380 blood samples, the dd-cfDNA median value was 0.21% (interquartile range 0.12%-0.39%) and the 97.5th percentile was 1.20%. In 18 patients with an average of 4.1 tests, the CVI was 21%, CVG was 37%, II was 0.57, and RCV was 61%. CONCLUSIONS: In a renal transplant recipient, a dd-cfDNA level above 1.2% is out of range and potentially abnormal. A serial increase of up to 61% in level of dd-cfDNA in a patient may be attributable to biological variation.Clinicaltrials.gov Identifier: NCT02424227.

Validation of a Clinical-Grade Assay to Measure Donor-Derived Cell-Free DNA in Solid Organ Transplant Recipients.

The use of circulating cell-free DNA (cfDNA) as a biomarker in transplant recipients offers advantages over invasive tissue biopsy as a quantitative measure for detection of transplant rejection and immunosuppression optimization. However, the fraction of donor-derived cfDNA (dd-cfDNA) in transplant recipient plasma is low and challenging to quantify. Previously reported methods to measure dd-cfDNA require donor and recipient genotyping, which is impractical in clinical settings and adds cost. We developed a targeted next-generation sequencing assay that uses 266 single-nucleotide polymorphisms to accurately quantify dd-cfDNA in transplant recipients without separate genotyping. Analytical performance of the assay was characterized and validated using 1117 samples comprising the National Institute for Standards and Technology Genome in a Bottle human reference genome, independently validated reference materials, and clinical samples. The assay quantifies the fraction of dd-cfDNA in both unrelated and related donor-recipient pairs. The dd-cfDNA assay can reliably measure dd-cfDNA (limit of blank, 0.10%; limit of detection, 0.16%; limit of quantification, 0.20%) across the linear quantifiable range (0.2% to 16%) with across-run CVs of 6.8%. Precision was also evaluated for independently processed clinical sample replicates and is similar to across-run precision. Application of the assay to clinical samples from heart transplant recipients demonstrated increased levels of dd-cfDNA in patients with biopsy-confirmed rejection and decreased levels of dd-cfDNA after successful rejection treatment. This noninvasive clinical-grade sequencing assay can be completed within 3 days, providing the practical turnaround time preferred for transplanted organ surveillance.

Gene expression profiling to study racial differences after heart transplantation.

BACKGROUND: The basis for increased mortality after heart transplantation in African Americans and other non-Caucasian racial groups is poorly defined. We hypothesized that increased risk of adverse events is driven by biologic factors. To test this hypothesis in the Invasive Monitoring Attenuation through Gene Expression (IMAGE) study, we determined whether the event rate of the primary outcome of acute rejection, graft dysfunction, death, or retransplantation varied by race as a function of calcineurin inhibitor (CNI) levels and gene expression profile (GEP) scores. METHODS: We determined the event rate of the primary outcome, comparing racial groups, stratified by time after transplant. Logistic regression was used to compute the relative risk across racial groups, and linear modeling was used to measure the dependence of CNI levels and GEP score on race. RESULTS: In 580 patients monitored for a median of 19 months, the incidence of the primary end point was 18.3% in African Americans, 22.2% in other non-Caucasians, and 8.5% in Caucasians (p < 0.001). There were small but significant correlations of race and tacrolimus trough levels to the GEP score. Tacrolimus levels were similar among the races. Of patients receiving tacrolimus, other non-Caucasians had higher GEP scores than the other racial groups. African American recipients demonstrated a unique decrease in expression of the FLT3 gene in response to higher tacrolimus levels. CONCLUSIONS: African Americans and other non-Caucasian heart transplant recipients were 2.5-times to 3-times more likely than Caucasians to experience outcome events in the Invasive Monitoring Attenuation through Gene Expression study. The increased risk of adverse outcomes may be partly due to the biology of the alloimmune response, which is less effectively inhibited at similar tacrolimus levels in minority racial groups.

Utility of gene expression profiling score variability to predict clinical events in heart transplant recipients.

BACKGROUND: Gene expression profiling test scores have primarily been used to identify heart transplant recipients who have a low probability of rejection at the time of surveillance testing. We hypothesized that the variability of gene expression profiling test scores within a patient may predict risk of future events of allograft dysfunction or death. METHOD: Patients from the IMAGE study with rejection surveillance gene expression profiling tests performed at 1- to 6-month intervals were selected for this cohort study. Gene expression profiling score variability was defined as the standard deviation of an individual's cumulative test scores. Gene expression profiling ordinal score (range, 0-39), threshold score (binary value=1 if ordinal score ≥ 34), and score variability were studied in multivariate Cox regression models to predict future clinical events. RESULTS: Race, age at time of transplantation, and time posttransplantation were significantly associated with future events in the univariate analysis. In the multivariate analyses, gene expression profiling score variability, but not ordinal scores or scores over threshold, was independently associated with future clinical events. The regression coefficient P values were <0.001, 0.46, and 0.773, for gene expression profiling variability, ordinal, and threshold scores, respectively. The hazard ratio for a 1 unit increase in variability was 1.76 (95% CI, 1.4-2.3). DISCUSSION: The variability of a heart recipient's gene expression profiling test scores over time may provide prognostic utility. This information is independent of the probability of acute cellular rejection at the time of testing that is rendered from a single ordinal gene-expression profiling test score.

Total synthesis of (-)-ulapualide A, a novel tris-oxazole macrolide from marine nudibranchs, based on some biosynthesis speculation.

A new, second generation, total synthesis of ulapualide A (1), whose stereochemistry was recently determined from X-ray analysis of its complex with the protein actin, is described. The synthesis is designed and based on some speculation of the biosynthetic origin of the contiguous tris-oxazole unit in ulapualide A, alongside that of the related co-metabolites that contain only two oxazole rings, e.g. 6 and 7. The mono-oxazole carboxylic acid 67b and the mono-oxazole secondary 55b alcohol which, together, contain all of the 10 asymmetric centres in the natural metabolite, were first elaborated using a combination of contemporary asymmetric synthesis protocols. Esterification of 67b with 55b under Yamaguchi conditions gave the ester 77 which was then converted into the omega-amino acid 18a following simultaneous deprotection of the t-butyl ester and the N-Boc protecting groups. Macrolactamisation of 18a, using HATU, now gave the key intermediate macrolactam 17, containing two of the three oxazole rings in ulapualide A (1). A number of procedures were used to introduce the third oxazole ring in ulapualide A from 17, including: a) cyclodehydration to the oxazoline 78a followed by oxidation using nickel peroxide leading to 76; b) dehydration to the enamide 79, followed by conversion into the methoxyoxazoline 78b, via 80, and elimination of methanol from 78b using camphorsulfonic acid. The tris-oxazole macrolide 76 was next converted into the aldehyde 82b in four straightforward steps, which was then reacted with N-methylformamide, leading to the E-alkenylformamide 83. Removal of the TBDPS protection at C3 in 83 finally gave (-)-ulapualide A, whose 1H and 13C NMR spectroscopic data were indistinguishable from those obtained for naturally derived material. It is likely that the tris-oxazole unit in ulapualide A (1) is derived in nature from a cascade of cyclodehydrations from an acylated tris-serine precursor, e.g.9, followed by oxidation of the resulting tris-oxazoline intermediate, i.e.10. It is also plausible to speculate that the biosynthesis of metabolites related to ulapualide A, e.g. the bis-oxazole 6 and the imide 7, involve cyclisations of just two of the serine units in 9. These speculations were given some credence by carrying out pertinent interconversions involving the bis-oxazole amide 24, the enamide 25, the imide 26, the oxazoline 27 and the tris-oxazole 30 as model compounds. An alternative strategy to the tris-oxazole macrolide intermediate 76 was also examined, involving preliminary synthesis of the aldehyde 73, containing a shortened (C25-C34) side chain from 67b and 47b. A Wadsworth-Emmons olefination reaction between 73 and the phosphonate ester 74 led smoothly to the E-alkene 75, but we were not able to reduce selectively the conjugated enone group in 75 to 76 without simultaneous reduction of the oxazole alkene bond, using a variety of reagents and reaction conditions.