Combined Metagenomic Viral Detection and Donor-Derived Cell-Free DNA Quantification in Plasma From Kidney Transplant Recipients.

BACKGROUND: Kidney transplant recipients require potent immunosuppression and are predisposed to opportunistic infections, many of which have a viral etiology. Currently, viral assays detect and quantify single pathogens using PCR or qPCR. An unbiased sequencing method with comparable accuracy would allow simultaneous monitoring of multiple viral pathogens and nonpathogenic Anelloviridae. The quantification of donor-derived cell-free DNA (dd-cfDNA) is an established method for the detection of allograft rejection, and a single workflow combining dd-cfDNA quantification and viral detection represents an opportunity to improve patient monitoring and management. METHODS: Whole genome sequencing of cell-free DNA was performed using 1,980 plasma samples from 256 subjects enrolled in a multi-center study. Non-human sequences underwent reference-assisted assembly and taxonomic annotation of the viral DNA pathogens. RESULTS: Of the 1,980 samples tested, 1,453 (73.4%) had ≥1 viral detection(s), either a known viral pathogen or torque teno virus (TTV), with positivity rates generally declining 12-18 months post-transplant. Concordance of metagenomic NGS (mNGS) viral detection with qPCR detection was 97.7% (94.1% sensitivity, 98.2% specificity), and a linear relationship was demonstrated between mNGS viral quantitation and qPCR results. BK virus, cytomegalovirus, and Epstein-Barr virus were detected by sequencing up to 60 days prior to independently established clinical diagnoses. CONCLUSIONS: Whole-genome sequencing allows simultaneous quantification of dd-cfDNA as well as sensitive and early detection of viral infection through secondary analysis of the same sequencing results. In combination with dd-cfDNA, mNGS viral detection may provide additional pathogen surveillance results and serve as a useful biomarker for both over- and under-immunosuppression.

European Society of Organ Transplantation Consensus Statement on Testing for Non-Invasive Diagnosis of Kidney Allograft Rejection.

To address the need for improved biomarkers for kidney transplant rejection, European Society of Organ Transplantation (ESOT) convened a dedicated working group comprised of experts in kidney transplant biomarkers to review literature pertaining to clinical and subclinical acute rejection to develop guidelines in the screening and diagnosis of acute rejection that were subsequently discussed and voted on during the Consensus Conference that took place in person in Prague. The findings and recommendations of the Working Group on Molecular Biomarkers of Kidney Transplant Rejection are presented in this article.

Combining Blood Gene Expression and Cellfree DNA to Diagnose Subclinical Rejection in Kidney Transplant Recipients.

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.