Kleiboeker, Steve

Background The primary objective of this analysis was to assess the association between non-invasive biomarker results within the first 2-years post-kidney transplant and 10-year All Cause Graft Loss (ACGL). Methods CTOT-08 was linked with the Scientific Registry of Transplant Recipients (SRTR) to assess 10-year ACGL. Cox Regression was used to determine the association between gene expression profile (GEP) and donor-derived cell-free DNA (dd-cfDNA) results and ACGL. A Cox Regression with time-varying covariates was used to test associations with ACGL with simultaneous and repeated biomarker results. Results The final landmarked Cox model included clinical acute rejection (aHR 2.58 (1,30,5.13) for 1 rejection, aHR 3.41 (1.07,10.85) for 2 rejections), diabetes (aHR 1.71 (0.99,2.96)), recipient age (aHR 1.02 (1.00,1.04)), the highest quartile of positive GEP (aHR 2.44 (1.45,4.10)) and the highest quartile of positive dd-cfDNA (aHR 2.91 (1.77,4.78)). In the time-varying model, having both biomarkers positive at the same time carried the greatest association with ACGL (aHR 4.29 (2.10,8.76)). Conclusions In this multicenter, prospective analysis of GEP and dd-cfDNA on patient and graft outcomes, an independent association with long-term ACGL was demonstrated. Further, a time-varying analysis demonstrated that two biomarkers with independent methodologies tested at the same time can provide more information than either one alone.

Key Points Peripheral blood biomarkers may have value in monitoring kidney transplant recipients after treatment of acute rejection. The donor-derived cellfree DNA may be more sensitive to identifying antibody-mediated rejection and gene expression profile may be more sensitive to identifying acute cellular rejection. Background Persistent rejection is an increasingly recognized barrier to long-term kidney allograft survival. A noninvasive method to help identify patients with persistent rejection in need of biopsy would be valuable. Methods This was a post hoc analysis of a multicenter observational study. Patients who had a biopsy-proven acute rejection, had another biopsy within 9 months (270 days), and had a biopsy-paired biomarker sample were included. Results A total of 64 index rejections in 58 patients with repeat biopsies were identified with a median time to repeat biopsy of 100 days. Persistent rejection was present in 61%; 69% of follow-up biopsies were performed in clinically stable patients. Peripheral blood gene expression profile (GEP) demonstrated a sensitivity of 59%, specificity of 76%, positive predictive value (PPV) of 79%, and negative predictive value of 54%. Donor-derived cellfree DNA (dd-cfDNA) demonstrated a sensitivity of 62%, specificity of 86%, PPV of 88%, and negative predictive value of 56%. For repeat biopsies within 90 days of rejection in clinically stable patients (63% of repeat biopsies), both GEP and dd-cfDNA had specificities and PPVs of 100%. GEP was more likely to be positive in T-cell–mediated rejection while dd-cfDNA was more likely to be positive in antibody-mediated rejection. Conclusions Both GEP and dd-cfDNA may have utility in identifying clinically stable patients with persistent rejection in need of biopsy; however, they identify different types of rejections. Clinical Trial registration number: NCT01531257.

Background and objectives Subclinical acute rejection is associated with poor outcomes in kidney transplant recipients. As an alternative to surveillance biopsies, noninvasive screening has been established with a blood gene expression profile. Donor-derived cellfree DNA (cfDNA) has been used to detect rejection in patients with allograft dysfunction but not tested extensively in stable patients. We hypothesized that we could complement noninvasive diagnostic performance for subclinical rejection by combining a donor-derived cfDNA and a gene expression profile assay. Design, setting, participants, & measurements We performed a post hoc analysis of simultaneous blood gene expression profile and donor-derived cfDNA assays in 428 samples paired with surveillance biopsies from 208 subjects enrolled in an observational clinical trial (Clinical Trials in Organ Transplantation-08). Assay results were analyzed as binary variables, and then, their continuous scores were combined using logistic regression. The performance of each assay alone and in combination was compared. Results For diagnosing subclinical rejection, the gene expression profile demonstrated a negative predictive value of 82%, a positive predictive value of 47%, a balanced accuracy of 64%, and an area under the receiver operating curve of 0.75. The donor-derived cfDNA assay showed similar negative predictive value (84%), positive predictive value (56%), balanced accuracy (68%), and area under the receiver operating curve (0.72). When both assays were negative, negative predictive value increased to 88%. When both assays were positive, positive predictive value increased to 81%. Combining assays using multivariable logistic regression, area under the receiver operating curve was 0.81, significantly higher than the gene expression profile ( P <0.001) or donor-derived cfDNA alone ( P =0.006). Notably, when cases were separated on the basis of rejection type, the gene expression profile was significantly better at detecting cellular rejection (area under the receiver operating curve, 0.80 versus 0.62; P =0.001), whereas the donor-derived cfDNA was significantly better at detecting antibody-mediated rejection (area under the receiver operating curve, 0.84 versus 0.71; P =0.003). Conclusions A combination of blood-based biomarkers can improve detection and provide less invasive monitoring for subclinical rejection. In this study, the gene expression profile detected more cellular rejection, whereas donor-derived cfDNA detected more antibody-mediated rejection.