The Current State of Donor-Derived Cell-Free DNA Use in Allograft Monitoring in Kidney Transplantation

Renal transplantation is the definitive therapy for patients suffering from end-stage renal disease. Though there have been significant advances in immunosuppression in these patients, there is still up to 30% acute and subclinical rejection. Current standards employ lab markers of renal function and biopsy results for accurate diagnosis. However, donor derived cell-free DNA has been identified as a measurable lab test that may be able to adequately diagnose rejection at early stages, precluding the need for invasive procedures like biopsy. We obtained published data directly from companies that offer ddcfDNA assay tests and additionally conducted a literature review using databases like PUBMED and NIH U.S. National Library of Medicine. We comprehensively compare the most used ddcfDNA assays, delineate their respective limitations, and further explore future directions in the utility of ddcfDNA in renal transplant patients

Antibody Therapeutics as Interfering Agents in Flow Cytometry Crossmatch for Organ Transplantation

Donor–recipient matching is a highly individualized and complex component of solid organ transplantation. Flowcytometry crossmatching (FC-XM) is an integral step in the matching process that is used to detect pre-formed deleterious anti-donor immunoglobulin. Despite high sensitivity in detecting cell-bound immunoglobulin, FC-XM is not able to determine the source or function of immunoglobulins detected. Monoclonal antibody therapeutic agents used in a clinic can interfere with the interpretation of FC-XM. We combined data from the prospectively maintained Antibody Society database and Human Protein Atlas with a comprehensive literature review of PubMed to summarize known FC-XM-interfering antibody therapeutics and identify potential interferers. We identified eight unique FC-XM-interfering antibody therapeutics. Rituximab (anti-CD20) was the most-cited agent. Daratumuab (anti-CD38) was the newest reported agent. We identified 43 unreported antibody therapeutics that may interfere with FC-XM. As antibody therapeutic agents become more common, identifying and mitigating FC-XM interference will likely become an increased focus for transplant centers

Donor hepatitis C status is not associated with an increased risk of acute rejection in kidney transplantation

Introduction: In renal transplantation, donor hepatitis C virus (HCV) status is crucial to consider when selecting a recipient given the high likelihood of transmission. We analyzed the effect of donor HCV status on post-renal transplant rejection and virologic infectious outcomes using electronic health record data from multiple US health care organizations. Methods: Using real world data from electronic health records of renal transplant recipients, a propensity score-matched case-control study of one-year renal transplant outcomes was conducted on cohorts of HCV-negative recipients who received an organ from an HCV-positive donor (HCV D+/R-) versus from an HCV-negative donor (HCV D-/R-). Donor HCV positivity was defined as new recipient HCV positivity within 30 days post-transplant. Cohorts were matched by major risk factors for rejection including age, gender, race, etiologies of end-stage renal disease, dialysis dependence, donor type, induction immunosuppression, and virologic lab studies. The primary outcome was one-year incidence of rejection. Secondary outcomes included longitudinal measures of liver and kidney function, incidence of non-HCV viremia, and DAA treatment pathways and responses. Results: Data from 900 renal transplant recipients were analyzed, 450 subjects per group (D+/R-, D-/R-). Mean age at transplant was 57.1 ± 11.9 years, 60 % were male, and 38 % were African American. Kaplan-Meier analysis showed a significantly increased incidence of one-year rejection for HCV D-/R- compared to HCV D+/R- (16.6% vs 22.8 %, p = 0.02). This difference did not persist on a sub-analysis excluding subjects with delayed graft function (DGF) (16.3% vs 19.2 %, p = 0.25). Although mean eGFR was initially higher in HCV D+/R-, there were no significant differences in liver or kidney allograft function at 12 months. There was no significant difference for composite viremia (CMV/EBV/BK; 37.66% vs 31.60 %, p = 0.07). The most common DAA regimen was glecaprevir/pibrentasvir (52.8 %). DAA treatment responses were excellent, with most subjects having a negative viral load by 90 days (mean: 1.7 ± 1.9 log units/mL). Conclusion: Donor HCV positivity did not negatively impact one-year rejection outcomes post-renal transplantation. Importantly, this effect was not biased by age. Anti-HCV treatment was effective and liver and kidney function were excellent at one-year post-transplant. These data support the continued expansion of the donor pool by utilizing organs from HCV-positive donors in the era of anti-HCV direct-acting antiviral therapies

Predicting Liver Allograft Discard: The Discard Risk Index

Background An index that predicts liver allograft discard can effectively grade allografts and can be used to preferentially allocate marginal allografts to aggressive centers. The aim of this study is to devise an index to predict liver allograft discard using only risk factors available at the time of initial DonorNet offer. Methods Using univariate and multivariate analyses on a training set of 72 297 deceased donors, we identified independent risk factors for liver allograft discard. Multiple imputation was used to account for missing variables. Results We identified 15 factors as significant predictors of liver allograft discard; the most significant risk factors were: total bilirubin > 10 mg/dL (odds ratio [OR], 25.23; confidence interval [CI], 17.32-36.77), donation after circulatory death (OR, 14.13; CI, 13.30-15.01), and total bilirubin 5 to 10 mg/dL (OR, 7.57; 95% CI, 6.32-9.05). The resulting Discard Risk Index (DSRI) accurately predicted the risk of liver discard with a C statistic of 0.80. We internally validated the model with a validation set of 37 243 deceased donors and also achieved a 0.80 C statistic. At a DSRI at the 90th percentile, the discard rate was 50% (OR, 32.34; CI, 28.63-36.53), whereas at a DSRI at 10th percentile, only 3% of livers were discarded. Conclusions The use of the DSRI can help predict liver allograft discard. The DSRI can be used to effectively grade allografts and preferentially allocate marginal allografts to aggressive centers to maximize the donor yield and expedite allocation

Heterogeneity in intrahepatic macrophage populations and druggable target expression in patients with steatotic liver disease-related fibrosis

Background & Aims: Clinical trials for reducing fibrosis in steatotic liver disease (SLD) have targeted macrophages with variable results. We evaluated intrahepatic macrophages in patients with SLD to determine if activity scores or fibrosis stages influenced phenotypes and expression of druggable targets, such as CCR2 and galectin-3. Methods: Liver biopsies from controls or patients with minimal or advanced fibrosis were subject to gene expression analysis using nCounter to determine differences in macrophage-related genes (n = 30). To investigate variability among individual patients, we compared additional biopsies by staining them with multiplex antibody panels (CD68/CD14/CD16/CD163/Mac387 or CD163/CCR2/galectin-3/Mac387) followed by spectral imaging and spatial analysis. Algorithms that utilize deep learning/artificial intelligence were applied to create cell cluster plots, phenotype profile maps, and to determine levels of protein expression (n = 34). Results: Several genes known to be pro-fibrotic (e.g. CD206, TREM2, CD163, and ARG1) showed either no significant differences or significantly decreased with advanced fibrosis. Although marked variability in gene expression was observed in individual patients with cirrhosis, several druggable targets and their ligands (e.g. CCR2, CCR5, CCL2, CCL5, and LGALS3) were significantly increased when compared to patients with minimal fibrosis. Antibody panels identified populations that were significantly increased (e.g. Mac387+), decreased (e.g. CD14+), or enriched (e.g. interactions of Mac387) in patients that had progression of disease or advanced fibrosis. Despite heterogeneity in patients with SLD, several macrophage phenotypes and druggable targets showed a positive correlation with increasing NAFLD activity scores and fibrosis stages. Conclusions: Patients with SLD have markedly varied macrophage- and druggable target-related gene and protein expression in their livers. Several patients had relatively high expression, while others were like controls. Overall, patients with more advanced disease had significantly higher expression of CCR2 and galectin-3 at both the gene and protein levels. Impact and implications: Appreciating individual differences within the hepatic microenvironment of patients with SLD may be paramount to developing effective treatments. These results may explain why such a small percentage of patients have responded to macrophage-targeting therapies and provide additional support for precision medicine-guided treatment of chronic liver diseases