Through the Looking Glass: Unraveling the Stage-Shift of Acute Rejection in Renal Allografts.

Sub-optimal sensitivity and specificity in current allograft monitoring methodologies underscore the need for more accurate and reflexive immunosurveillance to uncover the flux in alloimmunity between allograft health and the onset and progression of rejection. QSant-a urine based multi-analyte diagnostic test-was developed to profile renal transplant health and prognosticate injury, risk of evolution, and resolution of acute rejection. Q-Score-the composite score, across measurements of DNA, protein and metabolic biomarkers in the QSant assay-enables this risk prognostication. The domain of immune quiescence-below a Q-Score threshold of 32-is well established, based on published AUC of 98% for QSant. However, the trajectory of rejection is variable, given that causality is multi-factorial. Injury and subtypes of rejection are captured by the progression of Q-Score. This publication explores the clinical utility of QSant across the alloimmunity gradient of 32-100 for the early diagnosis of allograft injury and rejection.

Urinary Biomarkers for Kidney Allograft Injury.

The current standard of serum creatinine and biopsy to monitor allograft health has many limitations. The most significant drawback of the current standard is the lack of sensitivity and specificity to allograft injuries, which are diagnosed only after significant damage to the allograft. Thus, it is of critical need to identify a biomarker that is sensitive and specific to the early detection of allograft injuries. Urine, as the direct renal ultrafiltrate that can be obtained noninvasively, directly reflects intrarenal processes in the allograft at greater accuracy than analysis of peripheral blood. We review transcriptomic, metabolomic, genomic, and proteomic discovery-based approaches to identifying urinary biomarkers for the noninvasive detection of allograft injuries, as well as the use of urine cell-free DNA in the QSant urine assay as a sensitive surrogate for the renal allograft biopsy for rejection diagnosis.

Serum brain-derived neurotrophic factor remains elevated after long term follow-up of combat veterans with chronic post-traumatic stress disorder.

Attempts to correlate blood levels of brain-derived neurotrophic factor (BDNF) with post-traumatic stress disorder (PTSD) have provided conflicting results. Some studies found a positive association between BDNF and PTSD diagnosis and symptom severity, while others found the association to be negative. The present study investigated whether serum levels of BDNF are different cross-sectionally between combat trauma-exposed veterans with and without PTSD, as well as whether longitudinal changes in serum BDNF differ as a function of PTSD diagnosis over time. We analyzed data of 270 combat trauma-exposed veterans (230 males, 40 females, average age: 33.29 ± 8.28 years) and found that, at the initial cross-sectional assessment (T0), which averaged 6 years after the initial exposure to combat trauma (SD=2.83 years), the PTSD positive group had significantly higher serum BDNF levels than the PTSD negative controls [31.03 vs. 26.95 ng/mL, t(268) = 3.921, p < 0.001]. This difference remained significant after excluding individuals with comorbid major depressive disorder, antidepressant users and controlling for age, gender, race, BMI, and time since trauma. Fifty-nine of the male veterans who participated at the first timepoint (T0) were re-assessed at follow-up evaluation (T1), approximately 3 years (SD=0.88 years) after T0. A one-way ANOVA comparing PTSD positive, "subthreshold PTSD" and control groups revealed that serum BDNF remained significantly higher in the PTSD positive group than the control group at T1 [30.05 vs 24.66 ng/mL, F(2, 56)= 3.420, p = 0.040]. Serum BDNF levels did not correlate with PTSD symptom severity at either time point within the PTSD group [r(128) = 0.062, p = 0.481 and r(28) = 0.157, p = 0.407]. Serum BDNF did not significantly change over time within subjects [t(56) = 1.269, p = 0.210] nor did the change of serum BDNF from T0 to T1 correlate with change in PTSD symptom severity within those who were diagnosed with PTSD at T0 [r(27) = -0.250, p = 0.192]. Our longitudinal data are the first to be reported in combat PTSD and suggest that higher serum BDNF levels may be a stable biological characteristic of chronic combat PTSD independent of symptom severity.

A large staghorn stone diagnosed and managed in an asymptomatic patient using the "Kidney Injury Test (Kit)" spot urine assay: A case report.

The Kidney Injury Test (KIT) Stone-Score provides an objective measure of stone burden. Unlike urinary supersaturation the KIT Stone-Scores assess underlying stone disease rather than urinary solute composition. We report a case of a 43-year-old woman with no history of nephrolithiasis who underwent an elective, voluntary KIT assay and was diagnosed with a large staghorn renal stone after an unanticipated markedly elevated score. This clinical scenario highlights the potential future use of the non-invasive urinary KIT assay as a reliable non-invasive tool to detect and monitor urinary stone disease.

Clinical and Analytical Validation of a Novel Urine-Based Test for the Detection of Allograft Rejection in Renal Transplant Patients.

In this clinical validation study, we developed and validated a urinary Q-Score generated from the quantitative test QSant, formerly known as QiSant, for the detection of biopsy-confirmed acute rejection in kidney transplants. Using a cohort of 223 distinct urine samples collected from three independent sites and from both adult and pediatric renal transplant patients, we examined the diagnostic utility of the urinary Q-Score for detection of acute rejection in renal allografts. Statistical models based upon the measurements of the six QSant biomarkers (cell-free DNA, methylated-cell-free DNA, clusterin, CXCL10, creatinine, and total protein) generated a renal transplant Q-Score that reliably differentiated stable allografts from acute rejections in both adult and pediatric renal transplant patients. The composite Q-Score was able to detect both T cell-mediated rejection and antibody-mediated rejection patients and differentiate them from stable non-rejecting patients with a receiver-operator characteristic curve area under the curve of 99.8% and an accuracy of 98.2%. Q-Scores < 32 indicated the absence of active rejection and Q-Scores ≥ 32 indicated an increased risk of active rejection. At the Q-Score cutoff of 32, the overall sensitivity was 95.8% and specificity was 99.3%. At a prevalence of 25%, positive and negative predictive values for active rejection were 98.0% and 98.6%, respectively. The Q-Score also detected subclinical rejection in patients without an elevated serum creatinine level but identified by a protocol biopsy. This study confirms that QSant is an accurate and quantitative measurement suitable for routine monitoring of renal allograft status.

Targeted Urine Metabolomics for Monitoring Renal Allograft Injury and Immunosuppression in Pediatric Patients.

Despite new advancements in surgical tools and therapies, exposure to immunosuppressive drugs related to non-immune and immune injuries can cause slow deterioration and premature failure of organ transplants. Diagnosis of these injuries by non-invasive urine monitoring would be a significant clinical advancement for patient management, especially in pediatric cohorts. We investigated the metabolomic profiles of biopsy matched urine samples from 310 unique kidney transplant recipients using gas chromatography-mass spectrometry (GC-MS). Focused metabolite panels were identified that could detect biopsy confirmed acute rejection with 92.9% sensitivity and 96.3% specificity (11 metabolites) and could differentiate BK viral nephritis (BKVN) from acute rejection with 88.9% sensitivity and 94.8% specificity (4 metabolites). Overall, targeted metabolomic analyses of biopsy-matched urine samples enabled the generation of refined metabolite panels that non-invasively detect graft injury phenotypes with high confidence. These urine biomarkers can be rapidly assessed for non-invasive diagnosis of specific transplant injuries, opening the window for precision transplant medicine.

A urine score for noninvasive accurate diagnosis and prediction of kidney transplant rejection.

Accurate and noninvasive monitoring of renal allograft posttransplant is essential for early detection of acute rejection (AR) and to affect the long-term survival of the transplant. We present the development and validation of a noninvasive, spot urine-based diagnostic assay based on measurements of six urinary DNA, protein, and metabolic biomarkers. The performance of this assay for detecting kidney injury in both native kidneys and renal allografts is presented on a cohort of 601 distinct urine samples. The urinary composite score enables diagnosis of AR, with a receiver-operator characteristic curve area under the curve of 0.99 and an accuracy of 96%. In addition, we demonstrate the clinical utility of this assay for predicting AR before a rise in the serum creatinine, enabling earlier detection of rejection than currently possible by standard of care tests. This noninvasive, sensitive, and quantitative approach is a robust and informative method for the rapid and routine monitoring of renal allografts.

Use of the Tissue Common Rejection Module Score in Kidney Transplant as an Objective Measure of Allograft Inflammation.

Long-term kidney transplant (KT) allograft outcomes have not improved as expected despite a better understanding of rejection and improved immunosuppression. Previous work had validated a computed rejection score, the tissue common rejection module (tCRM), measured by amplification-based assessment of 11 genes from formalin-fixed paraffin-embedded (FFPE) biopsy specimens, which allows for quantitative, unbiased assessment of immune injury. We applied tCRM in a prospective trial of 124 KT recipients, and contrasted assessment by tCRM and histology reads from 2 independent pathologists on protocol and cause biopsies post-transplant. Four 10-µm shaves from FFPE biopsy specimens were used for RNA extraction and amplification by qPCR of the 11 tCRM genes, from which the tCRM score was calculated. Biopsy diagnoses of either acute rejection (AR) or borderline rejection (BL) were considered to have inflammation present, while stable biopsies had no inflammation. Of the 77 biopsies that were read by both pathologists, a total of 40 mismatches in the diagnosis were present. The median tCRM scores for AR, BL, and stable diagnoses were 4.87, 1.85, and 1.27, respectively, with an overall significant difference among all histologic groups (Kruskal-Wallis, p < 0.0001). There were significant differences in tCRM scores between pathologists both finding inflammation vs. disagreement (p = 0.003), and both finding inflammation vs. both finding no inflammation (p < 0.001), along with overall significance between all scores (Kruskal-Wallis, p < 0.001). A logistic regression model predicting graft inflammation using various clinical predictor variables and tCRM revealed the tCRM score as the only significant predictor of graft inflammation (OR: 1.90, 95% CI: 1.40-2.68, p < 0.0001). Accurate, quantitative, and unbiased assessment of rejection of the clinical sample is critical. Given the discrepant diagnoses between pathologists on the same samples, individuals could utilize the tCRM score as a tiebreaker in unclear situations. We propose that the tCRM quantitative score can provide unbiased quantification of graft inflammation, and its rapid evaluation by PCR on the FFPE shave can become a critical adjunct to help drive clinical decision making and immunosuppression delivery.

Non-radiological assessment of kidney stones using the kidney injury test (KIT), a spot urine assay.

OBJECTIVES: To evaluate the utility of kidney injury test (KIT) assay urinary biomarkers to detect kidney stones and quantify stone burden. PATIENTS AND METHODS: A total of 136 spot urine samples from 98 individuals, with and without kidney stone disease, were processed in a predefined assay to measure six DNA and protein markers in order to generate a risk score for the non-invasive detection of nephrolithiasis. From this cohort, 56 individuals had spot, non-timed urine samples collected at the time of radiographically confirmed kidney stones, and 54 demographically matched, healthy controls without kidney stone disease also provided spot, non-timed urine samples. Sixteen individuals with persistent stone disease had more than one urine sample. Using a proprietary microwell-based KIT assay, we measured cell-free DNA (cfDNA), methylated cfDNA, clusterin, creatinine, protein and CXCL10. A KIT stone score was computed across all markers using the prior locked KIT algorithm. The KIT stone score, with a scale of 0 to 100, was then correlated with demographic variables, kidney stone burden, obstructive kidney stone disease, and urine solutes in 24-h urine collections. RESULTS: The scaled KIT stone score, a composite of all six biomarkers, readily discriminated individuals with current or prior radiographically confirmed kidney stones from healthy controls without kidney stone disease (P < 0.001). In individuals with nephrolithiasis, KIT stone score also correlated with radiologically measured stone size (P = 0.017) and differentiated patients with a clinical radiological diagnosis of obstructive nephrolithiasis associated with upper renal tract dilatation (P = 0.001). Stone burden as assessed by KIT stone score, however, did not correlate with the any of the traditional measures of 24-h urine solutes or the 24-h urine supersaturation levels. In patients with persistent stone disease, where multiple urine samples were collected over time and after different interventions, the use of KIT stone score could non-invasively track stone burden over time through a spot urine, non-timed urine sample. CONCLUSIONS: A random, spot urine-based assay, KIT stone score, can non-invasively detect, quantify and monitor current stone burden, and may thus minimize radiographic exposure for kidney stone detection. The KIT stone score assay may also help monitor stone recurrence risk for patients with nephrolithiasis, without the requirement for 24-h urine collections.

Noninvasive Urinary Monitoring of Progression in IgA Nephropathy.

Standard methods for detecting and monitoring of IgA nephropathy (IgAN) have conventionally required kidney biopsies or suffer from poor sensitivity and specificity. The Kidney Injury Test (KIT) Assay of urinary biomarkers has previously been shown to distinguish between various kidney pathologies, including chronic kidney disease, nephrolithiasis, and transplant rejection. This validation study uses the KIT Assay to investigate the clinical utility of the non-invasive detection of IgAN and predicting the progression of renal damage over time. The study design benefits from longitudinally collected urine samples from an investigator-initiated, multicenter, prospective study, evaluating the efficacy of corticosteroids versus Rituximab for preventing progressive IgAN. A total of 131 urine samples were processed for this study; 64 urine samples were collected from 34 IgAN patients, and urine samples from 64 demographically matched healthy controls were also collected; multiple urinary biomarkers consisting of cell-free DNA, methylated cell-free DNA, DMAIMO, MAMIMO, total protein, clusterin, creatinine, and CXCL10 were measured by the microwell-based KIT Assay. An IgA risk score (KIT-IgA) was significantly higher in IgAN patients as compared to healthy control (87.76 vs. 14.03, p < 0.0001) and performed better than proteinuria in discriminating between the two groups. The KIT Assay biomarkers, measured on a spot random urine sample at study entry could distinguish patients likely to have progressive renal dysfunction a year later. These data support the pursuit of larger prospective studies to evaluate the predictive performance of the KIT-IgA score in both screening for non-invasive diagnosis of IgAN, and for predicting risk of progressive renal disease from IgA and utilizing the KIT score for potentially evaluating the efficacy of IgAN-targeted therapies.

A Novel Multi-Biomarker Assay for Non-Invasive Quantitative Monitoring of Kidney Injury.

The current standard of care measures for kidney function, proteinuria, and serum creatinine (SCr) are poor predictors of early-stage kidney disease. Measures that can detect chronic kidney disease in its earlier stages are needed to enable therapeutic intervention and reduce adverse outcomes of chronic kidney disease. We have developed the Kidney Injury Test (KIT) and a novel KIT Score based on the composite measurement and validation of multiple biomarkers across a unique set of 397 urine samples. The test is performed on urine samples that require no processing at the site of collection and without target sequencing or amplification. We sought to verify that the pre-defined KIT test, KIT Score, and clinical thresholds correlate with established chronic kidney disease (CKD) and may provide predictive information on early kidney injury status above and beyond proteinuria and renal function measurements alone. Statistical analyses across six DNA, protein, and metabolite markers were performed on a subset of residual spot urine samples with CKD that met assay performance quality controls from patients attending the clinical labs at the University of California, San Francisco (UCSF) as part of an ongoing IRB-approved prospective study. Inclusion criteria included selection of patients with confirmed CKD and normal healthy controls; exclusion criteria included incomplete or missing information for sample classification, logistical delays in transport/processing of urine samples or low sample volume, and acute kidney injury. Multivariate logistic regression of kidney injury status and likelihood ratio statistics were used to assess the contribution of the KIT Score for prediction of kidney injury status and stage of CKD as well as assess the potential contribution of the KIT Score for detection of early-stage CKD above and beyond traditional measures of renal function. Urine samples were processed by a proprietary immunoprobe for measuring cell-free DNA (cfDNA), methylated cfDNA, clusterin, CXCL10, total protein, and creatinine. The KIT Score and stratified KIT Score Risk Group (high versus low) had a sensitivity and specificity for detection of kidney injury status (healthy or CKD) of 97.3% (95% CI: 94.6-99.3%) and 94.1% (95% CI: 82.3-100%). In addition, in patients with normal renal function (estimated glomerular filtration rate (eGFR) ≥ 90), the KIT Score clearly identifies those with predisposing risk factors for CKD, which could not be detected by eGFR or proteinuria (p < 0.001). The KIT Score uncovers a burden of kidney injury that may yet be incompletely recognized, opening the door for earlier detection, intervention and preservation of renal function.

Cell-Free DNA and CXCL10 Derived from Bronchoalveolar Lavage Predict Lung Transplant Survival.

Standard methods for detecting chronic lung allograft dysfunction (CLAD) and rejection have poor sensitivity and specificity and have conventionally required bronchoscopies and biopsies. Plasma cell-free DNA (cfDNA) has been shown to be increased in various types of allograft injury in transplant recipients and CXCL10 has been reported to be increased in the lung tissue of patients undergoing CLAD. This study used a novel cfDNA and CXCL10 assay to evaluate the noninvasive assessment of CLAD phenotype and prediction of survival from bronchoalveolar lavage (BAL) fluid. A total of 60 BAL samples (20 with bronchiolitis obliterans (BOS), 20 with restrictive allograft syndrome (RAS), and 20 with stable allografts (STA)) were collected from 60 unique lung transplant patients; cfDNA and CXCL10 were measured by the ELISA-based KIT assay. Median cfDNA was significantly higher in BOS patients (6739 genomic equivalents (GE)/mL) versus STA (2920 GE/mL) and RAS (4174 GE/mL) (p < 0.01 all comparisons). Likelihood ratio tests revealed a significant association of overall survival with cfDNA (p = 0.0083), CXCL10 (p = 0.0146), and the interaction of cfDNA and CXCL10 (p = 0.023) based on multivariate Cox proportional hazards regression. Dichotomizing patients based on the median cfDNA level controlled for the mean level of CXCL10 revealed an over two-fold longer median overall survival time in patients with low levels of cfDNA. The KIT assay could predict allograft survival with superior performance compared with traditional biomarkers. These data support the pursuit of larger prospective studies to evaluate the predictive performance of cfDNA and CXCL10 prior to lung allograft failure.

Optimizing Detection of Kidney Transplant Injury by Assessment of Donor-Derived Cell-Free DNA via Massively Multiplex PCR.

Standard noninvasive methods for detecting renal allograft rejection and injury have poor sensitivity and specificity. Plasma donor-derived cell-free DNA (dd-cfDNA) has been reported to accurately detect allograft rejection and injury in transplant recipients and shown to discriminate rejection from stable organ function in kidney transplant recipients. This study used a novel single nucleotide polymorphism (SNP)-based massively multiplexed PCR (mmPCR) methodology to measure dd-cfDNA in various types of renal transplant recipients for the detection of allograft rejection/injury without prior knowledge of donor genotypes. A total of 300 plasma samples (217 biopsy-matched: 38 with active rejection (AR), 72 borderline rejection (BL), 82 with stable allografts (STA), and 25 with other injury (OI)) were collected from 193 unique renal transplant patients; dd- cfDNA was processed by mmPCR targeting 13,392 SNPs. Median dd-cfDNA was significantly higher in samples with biopsy-proven AR (2.3%) versus BL (0.6%), OI (0.7%), and STA (0.4%) (p < 0.0001 all comparisons). The SNP-based dd-cfDNA assay discriminated active from non-rejection status with an area under the curve (AUC) of 0.87, 88.7% sensitivity (95% CI, 77.7⁻99.8%) and 72.6% specificity (95% CI, 65.4⁻79.8%) at a prespecified cutoff (>1% dd-cfDNA). Of 13 patients with AR findings at a routine protocol biopsy six-months post transplantation, 12 (92%) were detected positive by dd-cfDNA. This SNP-based dd-cfDNA assay detected allograft rejection with superior performance compared with the current standard of care. These data support the feasibility of using this assay to detect disease prior to renal failure and optimize patient management in the case of allograft injury.

Transcriptional Perturbations in Graft Rejection.

BACKGROUND: Understanding the regulatory interplay of relevant microRNAs (miRNAs) and messenger RNAs (mRNAs) in the rejecting allograft will result in a better understanding of the molecular pathophysiology of alloimmune injury. METHODS: One hundred sixty-seven allograft biopsies, with (n = 47) and without (n = 120) central histology for Banff scored acute rejection (AR), were transcriptionally profiled for mRNA and miRNA by whole genome microarrays and multiplexed microfluidic quantitative polymerase chain reaction, respectively. A customized database was curated (GO-Elite) and used to identify AR-specific dysregulated mRNAs and the role of perturbations of their relevant miRNAs targets during AR. RESULTS: The AR-specific changes in 1035 specific mRNAs were mirrored by AR-specific perturbations in 9 relevant miRNAs as predicted by Go-Elite and were regulated specifically by p53 and forkhead box P3. Infiltrating lymphocytes and the renal tubules drove the miRNA tissue pertubations in rejection, involving message degradation and transcriptional/translational activation. The expression of many of these miRNAs significantly associated with the intensity of the Banff-scored interstitial inflammation and tubulitis. CONCLUSIONS: There is a highly regulated interplay between specific mRNA/miRNAs in allograft rejection that drive both immune-mediated injury and tissue repair during AR.