Friedewald, John J.

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.

Background. Long-term outcomes in kidney transplantation remain suboptimal, with subclinical acute rejection (subAR) frequently going undetected by conventional methods. We hypothesized that subAR represents a molecular precursor to clinical acute rejection (cAR). Leveraging a large National Institutes of Health-funded cohort with matched kidney tissue and peripheral blood samples, our primary objective was to determine whether subAR and cAR share molecular patterns, establishing subAR as an early stage of cAR. As a secondary aim, we compared biopsy and blood gene expression profiles to identify unique and shared pathways and to assess their diagnostic utility. Methods. This was a retrospective analysis of gene expression data from an observational clinical trial. We analyzed 578 blood and biopsy samples from 129 kidney transplant recipients enrolled in a multicenter observational study. Gene expression differences were analyzed using ANOVA with false discovery rate correction and molecular pathways analysis. Samples were matched and classified based on histologic findings and blood-based molecular diagnostics. Results. Gene expression and pathway analyses revealed that subAR exhibits a molecular profile consistent with a milder form of clinical rejection in both tissue and blood. Molecular signatures distinguished immune-mediated injury from nonimmune injury. Notably, tissue gene expression profiling in cases that were misclassified by peripheral blood diagnostics were like correctly classified cases, suggesting that histology alone may not reliably define true clinical phenotypes. Conclusions. Molecular profiling of tissue and blood reflects distinct but complementary aspects of transplant biology and confirms that subAR and cAR share overlapping molecular profiles, supporting the hypothesis that subAR represents an early stage in the progression toward clinical rejection. These findings highlight the limitations of relying solely on histological evaluation and support the use of molecular tissue profiling as an adjunct to histology, particularly in diagnostically ambiguous cases. Molecular profiling provides a supporting framework for identifying subclinical rejection and guiding personalized immunosuppression to improve long-term outcomes.

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.

Significance Statement Why are there so few biomarkers accepted by health authorities and implemented in clinical practice, despite the high and growing number of biomaker studies in medical research ? In this meta-epidemiological study, including 804 studies that were critically appraised by expert reviewers, the authors have identified all prognostic kidney transplant biomarkers and showed overall suboptimal study designs, methods, results, interpretation, reproducible research standards, and transparency. The authors also demonstrated for the first time that the limited number of studies challenged the added value of their candidate biomarkers against standard-of-care routine patient monitoring parameters. Most biomarker studies tended to be single-center, retrospective studies with a small number of patients and clinical events. Less than 5% of the studies performed an external validation. The authors also showed the poor transparency reporting and identified a data beautification phenomenon. These findings suggest that there is much wasted research effort in transplant biomarker medical research and highlight the need to produce more rigorous studies so that more biomarkers may be validated and successfully implemented in clinical practice. Background Despite the increasing number of biomarker studies published in the transplant literature over the past 20 years, demonstrations of their clinical benefit and their implementation in routine clinical practice are lacking. We hypothesized that suboptimal design, data, methodology, and reporting might contribute to this phenomenon. Methods We formed a consortium of experts in systematic reviews, nephrologists, methodologists, and epidemiologists. A systematic literature search was performed in PubMed, Embase, Scopus, Web of Science, and Cochrane Library between January 1, 2005, and November 12, 2022 (PROSPERO ID: CRD42020154747). All English language, original studies investigating the association between a biomarker and kidney allograft outcome were included. The final set of publications was assessed by expert reviewers. After data collection, two independent reviewers randomly evaluated the inconsistencies for 30% of the references for each reviewer. If more than 5% of inconsistencies were observed for one given reviewer, a re-evaluation was conducted for all the references of the reviewer. The biomarkers were categorized according to their type and the biological milieu from which they were measured. The study characteristics related to the design, methods, results, and their interpretation were assessed, as well as reproducible research practices and transparency indicators. Results A total of 7372 publications were screened and 804 studies met the inclusion criteria. A total of 1143 biomarkers were assessed among the included studies from blood ( n =821, 71.8%), intragraft ( n =169, 14.8%), or urine ( n =81, 7.1%) compartments. The number of studies significantly increased, with a median, yearly number of 31.5 studies (interquartile range [IQR], 23.8–35.5) between 2005 and 2012 and 57.5 (IQR, 53.3–59.8) between 2013 and 2022 ( P < 0.001). A total of 655 studies (81.5%) were retrospective, while 595 (74.0%) used data from a single center. The median number of patients included was 232 (IQR, 96–629) with a median follow-up post-transplant of 4.8 years (IQR, 3.0–6.2). Only 4.7% of studies were externally validated. A total of 346 studies (43.0%) did not adjust their biomarker for key prognostic factors, while only 3.1% of studies adjusted the biomarker for standard-of-care patient monitoring factors. Data sharing, code sharing, and registration occurred in 8.8%, 1.1%, and 4.6% of studies, respectively. A total of 158 studies (20.0%) emphasized the clinical relevance of the biomarker, despite the reported nonsignificant association of the biomarker with the outcome measure. A total of 288 studies assessed rejection as an outcome. We showed that these rejection studies shared the same characteristics as other studies. Conclusions Biomarker studies in kidney transplantation lack validation, rigorous design and methodology, accurate interpretation, and transparency. Higher standards are needed in biomarker research to prove the clinical utility and support clinical use.

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.

Abstract The authors have requested that this preprint be removed from Research Square.

Introduction: Because apolipoprotein L1 ( APOL1) risk variants may contribute to live donors’ kidney failure postdonation, professional guidelines suggest informing potential donors with African ancestry about the availability of APOL1 genotyping. This study assessed African American (AA) donors’ perceptions of APOL1 genetic testing and how APOL1 may affect ethnic identity. Methods/Approach: Four focus groups were conducted with AA donors about their decision-making for and perceptions of APOL1 genetic testing and donation to inform a new culturally targeted educational brochure on APOL1 genetic testing. Qualitative data were analyzed by thematic analysis. Findings: Seventeen donors participated (47% participation rate). Four major themes emerged. (1) In hypothetical scenarios, most participants would have undergone APOL1 testing during donor evaluation to make a more informed decision, but many would have still donated. (2) Participants desired information about how having 2 APOL1 risk variants affects the donor’s and the recipient’s health. (3) Participants referred to diversity of genetic ancestry and cultural constructions of racial/ethnic identity to question the population at risk for APOL1 risk variants and recommended that all potential donors undergo genetic testing and receive education about APOL1. (4) Participants worried that out-of-pocket costs would deter APOL1 testing and that APOL1 could become a preexisting condition and discriminate against AAs. Discussion: Our findings suggest that AA donors desire APOL1 testing to foster informed consent. Transplant clinicians should be aware of these responses to APOL1 testing and be sensitive to historical issues of distrust and discrimination.

Background. Underutilization of marginal-quality kidneys for transplantation produced ideas of expediting kidney placement for populations with decreased opportunities of receiving transplants. Such policies can be less efficacious for specific individuals and should be scrutinized until the decision-making for accepting marginal-quality organs, which has relied on experiential judgment, is better understood at the individual level. There exist rigorous tools promoting personalized decisions with useful and objective information. Methods. This article introduces a decision-tree methodology that analyzes a patient’s dilemma: to accept a kidney offer now or reject it. The methodology calculates the survival benefit of accepting a kidney given a certain quality now and the survival benefit of rejecting it. Survival benefit calculation accounts for patients’ and donors’ characteristics and transplant centers’ and organ procurement organizations’ performances and incorporates patients’ perceived transplant and dialysis utilities. Valuations of rejecting an offer are contingent on future opportunities and subject to uncertainty in the timing of successive kidney offers and their quality and donor characteristics. Results. The decision tree was applied to a realistic patient profile as a demonstration. The tool was tested on 1000 deceased-donor kidney offers in 2016. Evaluating up to 1 year of future offers, the tool attains 61% accuracy, with transplant utility of 1.0 and dialysis utility of 0.5. The accuracy reveals potential bias in kidney offer acceptance/rejection at transplant centers. Conclusions. The decision-tree tool presented could aid personalized transplant decision-making in the future by providing patients with calculated, individualized survival benefits between accepting and rejecting a kidney offer.

Introduction: There is debate over whether Apolipoprotein L1 (APOL1) gene risk variants contribute to African American (AA) live donors’ (LD) increased risk of kidney failure. Little is known about factors influencing physicians’ integration of APOL1 genetic testing of AA LDs into donor evaluation. Design: We conducted a cross-sectional survey, informed by Roger’s Diffusion of Innovations theory, among nephrology and surgeon members of the American Society of Nephrology, American Society of Transplantation, and American Society of Transplant Surgeons about their practices of and attitudes about APOL1 genetic testing of AA potential LDs. Descriptive statistics and bivariate analyses were performed. Results: Of 383 completed surveys, most physicians believed that APOL1 testing can help AA LDs make more informed donation decisions (87%), and the addition of APOL1 testing offers better clinical information about AA LD’s eligibility for donation than existing evaluation approaches (74%). Among respondents who evaluate LDs (n = 345), 63% would definitely or probably begin or continue using APOL1 testing in the next year, however, few use APOL1 testing routinely (4%) or on a case-by-case basis (14%). Most did not know the right clinical scenario to order APOL1 testing (59%), but would use educational materials to counsel AA LDs about APOL1 testing (97%). Discussion: Although physicians were highly supportive of APOL1 genetic testing for AA LDs, few physicians use APOL1 testing. As more physicians intend to use APOL1 testing, an ethical framework and clinical decision support are needed presently to assist clinicians in clarifying the proper indication of APOL1 genetic testing.