Urine Metabolite Profiles Predictive of Human Kidney Allograft Status

Noninvasive diagnosis and prognostication of acute cellular rejection in the kidney allograft may help realize the full benefits of kidney transplantation. To investigate whether urine metabolites predict kidney allograft status, we determined levels of 749 metabolites in 1516 urine samples from 241 kidney graft recipients enrolled in the prospective multicenter Clinical Trials in Organ Transplantation-04 study. A metabolite signature of the ratio of 3-sialyllactose to xanthosine in biopsy specimen-matched urine supernatants best discriminated acute cellular rejection biopsy specimens from specimens without rejection. For clinical application, we developed a high-throughput mass spectrometry-based assay that enabled absolute and rapid quantification of the 3-sialyllactose-to-xanthosine ratio in urine samples. A composite signature of ratios of 3-sialyllactose to xanthosine and quinolinate to X-16397 and our previously reported urinary cell mRNA signature of 18S ribosomal RNA, CD3ε mRNA, and interferon-inducible protein-10 mRNA outperformed the metabolite signatures and the mRNA signature. The area under the receiver operating characteristics curve for the composite metabolite–mRNA signature was 0.93, and the signature was diagnostic of acute cellular rejection with a specificity of 84% and a sensitivity of 90%. The composite signature, developed using solely biopsy specimen-matched urine samples, predicted future acute cellular rejection when applied to pristine samples taken days to weeks before biopsy. We conclude that metabolite profiling of urine offers a noninvasive means of diagnosing and prognosticating acute cellular rejection in the human kidney allograft, and that the combined metabolite and mRNA signature is diagnostic and prognostic of acute cellular rejection with very high accuracy.     

Neutrophil gelatinase-associated lipocalin is a sensitive biomarker for the early diagnosis of acute rejection after living-donor kidney transplantation

Background

Early diagnosis of kidney allograft dysfunction is crucial for the management and long-term survival of transplanted kidneys. We investigated whether neutrophil gelatinase-associated lipocalin (NGAL), interleukin 18 (IL-18), and liver-type fatty acid-binding protein (L-FABP) are capable of being used as novel biomarkers of acute kidney allograft dysfunction.

Methods

We measured serum and urine NGAL, urine IL-18, and urine L-FABP levels on the first 3 days after transplantation. To assess the diagnostic sensitivity of these biomarkers, a receiver-operating characteristic curve (ROC) was plotted, and the area under the curve (AUC) was calculated to quantify the accuracy of the parameter. Sections from paraffin-embedded biopsy specimens were examined by immunohistochemistry for NGAL expression.

Results

Twelve cases were clinically diagnosed as acute rejection (AR) by renal biopsy. Urine NGAL was the most sensitive of these markers for detection of acute kidney allograft dysfunction. The cutoff value of urine NGAL was 66.0 ng/ml, with an AUC of 0.79 (95 % CI 0.68–0.88). Sensitivity of serum NGAL was about the same as urine NGAL with an AUC of 0.75 (0.64–0.85). IL-18 and L-FABP were 0.584 (95 % CI 0.433–0.725) and 0.612 (95 % CI 0.460–0.749), respectively. NGAL was more useful than other biomarkers to detect AR of kidney allograft dysfunction. NGAL staining intensity was significantly increased in the proximal tubules of the transplants with AR than in transplants that were not acutely rejected.

Conclusion

Urine NGAL level was found to be the most sensitive biomarker of acute kidney allograft dysfunction after living-donor kidney transplantation.     

Prediction of subclinical renal allograft rejection by vascular endothelial growth factor in serum and urine

BACKGROUND: Until now subclinical renal allograft rejection has only been recognized through a protocol biopsy. The aim of this study was to assess whether measurement of vascular endothelial growth factor (VEGF) in serum and urine could be adopted as a new noninvasive tool to predict subclinical rejection. METHODS: Concentration of VEGF in serum and urine was determined by ELISA in 132 recipients of a renal allograft with stable renal transplant function who were to undergo protocol biopsy and 80 healthy controls. A conventional receiver operating characteristic (ROC) curve was used to determine the sensitivities and specificities for patients with subclinical rejection. RESULTS: Levels of VEGF in serum (126.96 +/- 20.13 pg/mL; 95% confidence interval [95% CI], 83.10-170.83) and urine (16.14 +/- 4.09 ng/mmol creatinine; 95% CI, 7.21-25.06) of 13 patients with subclinical rejection significantly differed from those of 119 patients with no allograft rejection (No-AR) and health controls. The areas under the ROC curve were 0.771 (95% CI, 0.0.64-0.901) and 0.819 (95% CI, 0.662-0.976), respectively. Levels of VEGF in serum and urine after antirejection therapy (50.45 +/- 6.58 pg/mL and 2.60 +/- 0.83 ng/mmol creatinine, respectively) were lower than those at the time of protocol biopsy. No difference in urinary and serum VEGF expression was observed between cyclosporine and tacrolimus treatment. CONCLUSION: It is first reported that the monitoring of VEGF in serum and urine might be a new noninvasive approach to supplement a protocol biopsy for detection of subclinical rejection.     

Urinary Cell mRNA Profiles and Differential Diagnosis of Acute Kidney Graft Dysfunction

Noninvasive tests to differentiate the basis for acute dysfunction of the kidney allograft are preferable to invasive allograft biopsies. We measured absolute levels of 26 prespecified mRNAs in urine samples collected from kidney graft recipients at the time of for-cause biopsy for acute allograft dysfunction and investigated whether differential diagnosis of acute graft dysfunction is feasible using urinary cell mRNA profiles. We profiled 52 urine samples from 52 patients with biopsy specimens indicating acute rejection (26 acute T cell–mediated rejection and 26 acute antibody-mediated rejection) and 32 urine samples from 32 patients with acute tubular injury without acute rejection. A stepwise quadratic discriminant analysis of mRNA measures identified a linear combination of mRNAs for CD3ε, CD105, TLR4, CD14, complement factor B, and vimentin that distinguishes acute rejection from acute tubular injury; 10-fold cross-validation of the six-gene signature yielded an estimate of the area under the curve of 0.92 (95% confidence interval, 0.86 to 0.98). In a decision analysis, the six-gene signature yielded the highest net benefit across a range of reasonable threshold probabilities for biopsy. Next, among patients diagnosed with acute rejection, a similar statistical approach identified a linear combination of mRNAs for CD3ε, CD105, CD14, CD46, and 18S rRNA that distinguishes T cell–mediated rejection from antibody-mediated rejection, with a cross-validated estimate of the area under the curve of 0.81 (95% confidence interval, 0.68 to 0.93). Incorporation of these urinary cell mRNA signatures in clinical decisions may reduce the number of biopsies in patients with acute dysfunction of the kidney allograft.     

Urinary Exosomes as a Source of Kidney Dysfunction Biomarker in Renal Transplantation

End-stage renal disease (ESRD) requires for its treatment permanent dialysis or kidney transplantation (KT). KT is the best clinical treatment, however, the early function of the allograft varies depending on multiple factors associated with cold ischemia time (CIT) and the allograft rejection process. It is known that serum creatinine is an insensitive and late marker for predicting graft recovery after KT, mainly in patients with delayed graft function (DGF). Neutrophil gelatinase-associated lipocalin (NGAL) is produced in the distal nephron and it is one of the most promising novel biomarkers for acute kidney injury (AKI) and chronic kidney disease (CKD). NGAL has been proposed to be a predictor of organ recovery from DGF after KT from donors after cardiac death. Because nonrenal diseases can also induce NGAL, more information is necessary to validate the sensitivity and specificity of urine and plasma NGAL in clinical samples. The exosomes are vesicles released into the urine from the kidney epithelium and they have been proposed as better source to explore as biomarker of renal dysfunction. The molecular composition of the urinary exosomes could be representative of the physiological or physiopathologic condition of the urinary system. We propose that determination of NGAL in urinary exosomes is a better predictor of kidney dysfunction after KT than other urinary fractions. We analyzed 15 kidney allograft recipients, with a mean age of 36 years (range, 16–60 years) and 75% were male: 11 living donors (LD) and 4 deceased donors (DD). The average length of CIT was 14 hours in DD and less than 1 hour in LD. Three patient developed DGF. Using Western blot analysis, NGAL was detectable in the cellular and exosomal fraction of the urine. The exosomes expressed higher levels of NGAL than the cellular fraction. The expression of NGAL was observed from the first day after transplantation. In the cellular fraction of the urine, no significant differences of NGAL were observed between the patients. However, the median of NGAL expression in the exosomes fraction was significantly higher in DD patient, from the first day after KT (P < .05). Moreover, we noticed that NGAL expression in exosomes remained elevated in the patients with DGF compared with non-DGF patients (P < .05). Considering the highest abundance of NGAL in the urinary exosomes and its correlation with DGF patients, we suggest the exosomal fraction as a more sensitive substrate to evaluate early biomarkers of DGF after KT.     

Contrast between traditional and machine learning algorithms based on a urine culture predictive model: a multicenter retrospective study in patients with urinary calculi

BackgroundQuick and accurate identification of urinary calculi patients with positive urinary cultures is critical to the choice of the treatment strategy. Predictive models based on machine learning algorithms provide a new way to solve this problem. This study aims to determine the predictive value of machine learning algorithms using a urine culture predictive model based on patients with urinary calculi.MethodsData were collected from four clinical centers in the period of June 2016, to May 2019. 2,054 cases were included in the study. The dataset was randomly split into ratios of 5:5, 6:4, and 7:3 for model construction and validation. Predictive models of urine culture outcomes were constructed and validated by logistic regression, random forest, adaboost, and gradient boosting decision tree (GBDT) models. Each ratio’s construction and verification were repeated five times independently for cross-validation. The Matthews correlation coefficient (MMC), F1-score, receiver operating characteristic (ROC) curve with the area under curve (AUC) was used to evaluate the performance of each prediction model. The additive net reclassification index (NRI) and absolute NRI were used to assess the predictive capabilities of the models.ResultsFour prediction models of urinary culture results in patients with urinary calculi were constructed. The mean AUCs of the logistic regression, random forest, adaboost, and GBDT models were 0.761 (95% CI: 0.753–0.770), 0.790 (95% CI: 0.782–0.798), 0.779 (95% CI: 0.766–0.791), and 0.831 (95% CI: 0.823–0.840), respectively. Moreover, the average MMC and F1-score of GBDT model was 0.460 and 0.588, which was improved compared to logistic regression model of 0.335 and 0.501. The additive NRI and absolute NRI of the GBDT and logistic regression models were 0.124 (95% CI: 0.106–0.142) and 0.065 (95% CI: 0.060–0.069), respectively.ConclusionsOur results indicate that machine learning algorithms may be useful tools for urine culture outcome prediction in patients with urinary calculi because they exhibit superior performance compared with the logistic regression model.     

Urine proteomics in kidney transplantation

The transplanted kidney, through its urinary output, provides a medium through which the molecular constitution can provide insight into either the healthy function or developing dysfunction of a newly transplanted organ. An assay that would detect the aberration of early biomarkers of allograft injury using only urine samples from patients would provide many advantages over the current use of creatinine and tissue biopsies, as these means are either relatively non-specific or very invasive. Several urine biomarkers have been correlated with allograft injury, including CXCL9, CXCL10, CCL2, NGAL, IL-18, cystatin C, KIM-1 and Tim-3. The recent results of the CTOT-01 trial serve to validate the predictive value of the CXCL9 biomarker as a non-invasive biomarker for rejection and a prognostic indicator of graft function. There is now a preponderance of evidence showing a value of urinary monitoring of CXCL9 and CXCL10 with respect to detection of acute kidney allograft rejection. The value of the assay has been validated as a means of reducing the need for kidney transplant biopsy and applying biopsy in a more targeted manner. Additional goals for non-invasive monitoring would include predictive value prior to creatinine elevation that in turn would permit earlier, preemptive treatment of rejection.     

Machine learning-assisted decision-support models to better predict patients with calculous pyonephrosis

BackgroundTo develop a machine learning (ML)-assisted model capable of accurately identifying patients with calculous pyonephrosis before making treatment decisions by integrating multiple clinical characteristics.MethodsWe retrospectively collected data from patients with obstructed hydronephrosis who underwent retrograde ureteral stent insertion, percutaneous nephrostomy (PCN), or percutaneous nephrolithotomy (PCNL). The study cohort was divided into training and testing datasets in a 70:30 ratio for further analysis. We developed 5 ML-assisted models from 22 clinical features using logistic regression (LR), LR optimized by least absolute shrinkage and selection operator (Lasso) regularization (Lasso-LR), support vector machine (SVM), extreme gradient boosting (XGBoost), and random forest (RF). The area under the curve (AUC) was applied to determine the model with the highest discrimination. Decision curve analysis (DCA) was used to investigate the clinical net benefit associated with using the predictive models.ResultsA total of 322 patients were included, with 225 patients in the training dataset, and 97 patients in the testing dataset. The XGBoost model showed good discrimination with the AUC, accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 0.981, 0.991, 0.962, 1.000, 1.000, and 0.989, respectively, followed by SVM [AUC =0.985, 95% confidence interval (CI): 0.970–1.000], Lasso-LR (AUC =0.977, 95% CI: 0.958–0.996), LR (AUC =0.936, 95% CI: 0.905–0.968), and RF (AUC =0.920, 95% CI: 0.870–0.970). Validation of the model showed that SVM yielded the highest AUC (0.977, 95% CI: 0.952–1.000), followed by Lasso-LR (AUC =0.959, 95% CI: 0.921–0.997), XGBoost (AUC =0.958, 95% CI: 0.902–1.000), LR (AUC =0.932, 95% CI: 0.878–0.987), and RF (AUC =0.868, 95% CI: 0.779–0.958) in the testing dataset.ConclusionsOur ML-based models had good discrimination in predicting patients with obstructed hydronephrosis at high risk of harboring pyonephrosis, and the use of these models may be greatly beneficial to urologists in treatment planning, patient selection, and decision-making.     

血浆外泌体miR-210、miR-21和miR-4639对肾移植术后并发慢性移植肾肾病的诊断价值

目的检测肾移植受者术后血浆外泌体miR-21、miR-210和miR-4639表达变化，分析外泌体miR-21、miR-210和miR-4639单独及联合对肾移植术后并发慢性移植肾肾病(CAN)的诊断价值。 方法回顾性分析2018年1月至2019年1月苏州大学附属第三医院泌尿外科实施的同种异体肾移植受者临床资料，最终纳入34例受者，根据肾移植术后是否发生CAN将其分为CAN组及对照组。采用凝胶排阻色谱法提取血浆外泌体，采用Nanosight NS300分析外泌体粒径，采用蛋白质印迹法(WB)分析外泌体表面标志物(CD63和Alix)表达情况。采用卡方检验比较CAN组和对照组受者性别比例。采用成组t检验比较两组受者移植前年龄、末次血清肌酐、血清尿素氮和估算肾小球滤过率(eGFR)。采用受试者工作特征(ROC)曲线评价血浆外泌体miR-210、miR-21和miR-4639对肾移植术后并发CAN的诊断效能。P<0.05为差异有统计学意义。 结果CAN组(n＝18例)和对照组(n＝16例)受者性别以及移植前年龄、末次血清肌酐、血清尿素氮和eGFR差异均无统计学意义(χ²＝0.04、t＝0.86、-1.84、-1.83和0.85，P均>0.05)。透射电镜、Nanosight NS300及WB检测结果均提示提取样本为血浆外泌体。CAN组与对照组血浆外泌体miR-210、miR-21和miR-4639相对表达量差异均有统计学意义(t＝4.13、3.38和2.33，P均<0.05)。miR-210预测肾移植术后并发CAN的ROC曲线下面积为0.854(95%CI：0.730～0.979，P<0.05)，当截断值＝1.320时，敏感度为66.7%，特异度为93.8%。miR-21预测肾移植术后并发CAN的ROC曲线下面积为0.774(95%CI：0.618～0.931，P<0.05)，当截断值＝1.243时，敏感度为55.6%，特异度为93.8%。miR-4639预测肾移植术后并发CAN的ROC曲线下面积为0.670(95%CI：0.482～0.859，P<0.05)，当截断值＝0.936，敏感度为66.7%，特异度为75.0%。随后，构建基于miR-210、miR-21和miR-4639 3个指标的联合诊断模型，回归方程z＝5.293×[miR-210]＋5.046×[miR-21]＋0.433×[miR-4639]-13.373，联合预测概率值p＝e^z/(1＋e^z)。miR-210、miR-21和miR-4639联合预测肾移植术后并发CAN的ROC曲线下面积为0.938(95%CI：0.860～1.015，P<0.05)，当截断值＝0.587，敏感度为83.33%，特异度为93.75%。当联合预测值为0.587时，CAN组有83.3%(15/18)的个体被联合预测模型诊断出阳性结果，而对照组有93.8%(15/16)的个体被联合预测模型诊断出阴性结果，表明该联合预测模型有较好的诊断价值。 结论miR-210、miR-21和miR-4639组成的miRNA阵列可能可以用于早期诊断肾移植术后并发CAN。     

Validation of donor fraction cell-free DNA with biopsy-proven cardiac allograft rejection in children and adults

ObjectivesDonor-specific cell-free DNA shows promise as a noninvasive marker for allograft rejection, but as yet has not been validated in both adult and pediatric recipients. The study objective was to validate donor fraction cell-free DNA as a noninvasive test to assess for risk of acute cellular rejection and antibody-mediated rejection after heart transplantation in pediatric and adult recipients.MethodsPediatric and adult heart transplant recipients were enrolled from 7 participating sites and followed for 12 months or more with plasma samples collected immediately before all endomyocardial biopsies. Donor fraction cell-free DNA was extracted, and quantitative genotyping was performed. Blinded donor fraction cell-free DNA and clinical data were analyzed and compared with a previously determined threshold of 0.14%. Sensitivity, specificity, negative predictive value, positive predictive value, and receiver operating characteristic curves were calculated.ResultsA total of 987 samples from 144 subjects were collected. After applying predefined clinical and technical exclusions, 745 samples from 130 subjects produced 54 rejection samples associated with the composite outcome of acute cellular rejection grade 2R or greater and pathologic antibody-mediated rejection 2 or greater and 323 healthy samples. For all participants, donor fraction cell-free DNA at a threshold of 0.14% had a sensitivity of 67%, a specificity of 79%, a positive predictive value of 34%, and a negative predictive value of 94% with an area under the curve of 0.78 for detecting rejection. When analyzed independently, these results held true for both pediatric and adult cohorts at the same threshold of 0.14% (negative predictive value 92% and 95%, respectively).ConclusionsDonor fraction cell-free DNA at a threshold of 0.14% can be used to assess for risk of rejection after heart transplantation in both pediatric and adult patients with excellent negative predictive value.     

Increased Delta Neutrophil Index Is Associated With Poor Prognosis in Cadaver Donor Kidney Transplantation

ObjectiveDelta neutrophil index (DNI), representing an elevated fraction of circulating immature granulocyte in acute infection, has been reported as a useful, predictable marker for mortality in patients with sepsis. We have hypothesized that an increased recipient DNI is associated with poor prognosis in cadaver donor kidney transplantation.MethodsWe investigated patients undergoing kidney transplantation from cadaver donors from March 2013 to January 2018. Rejection was diagnosed by kidney biopsy with Banff classification and excluded subclinical rejection.ResultsIn a total of 73 patients undergoing cadaver kidney transplantation, 25 (34.2%) patients were diagnosed with rejection based on the Banff classification. Among them, 11 patients were diagnosed with early rejection. The recipients' postoperative DNI (%) was different between patients with early rejection and patients without rejection (0.18 vs 1.21, P < .001). In the univariate logistic regression analysis, cold ischemic time, donor preoperative last creatinine level, postoperative DNI level, and perioperative infection were predictive of early rejection. However, in a multivariate adjusted logistic regression test, only a high level of DNI (odds ratio 12.307, 95% confidence interval [CI] 1.22–129.82) was associated with early rejection. The C-statistic was 0.777 (95% CI 0.604–0.951, P = .004) for DNI. In multivariate Cox regression analysis, the donor's last creatinine level (hazard ratio 2.25, 95% CI 1.26–4.13) and preoperative DNI (hazard ratio 14.02 95% CI 2.62–75.26) were predictors of renal survival.ConclusionsIncreased DNI in cadaver donor kidney transplantation recipients might be one of the predictive values of early kidney rejection and prognosis.     

Urinary C-X-C Motif Chemokine 10 Independently Improves the Noninvasive Diagnosis of Antibody–Mediated Kidney Allograft Rejection

Urinary levels of C-X-C motif chemokine 9 (CXCL9) and CXCL10 can noninvasively diagnose T cell–mediated rejection (TCMR) of renal allografts. However, performance of these molecules as diagnostic/prognostic markers of antibody-mediated rejection (ABMR) is unknown. We investigated urinary CXCL9 and CXCL10 levels in a highly sensitized cohort of 244 renal allograft recipients (67 with preformed donor–specific antibodies [DSAs]) with 281 indication biopsy samples. We assessed the benefit of adding these biomarkers to conventional models for diagnosing/prognosing ABMR. Urinary CXCL9 and CXCL10 levels, normalized to urine creatinine (Cr) levels (CXCL9:Cr and CXCL10:Cr) or not, correlated with the extent of tubulointerstitial (i+t score; all P<0.001) and microvascular (g+ptc score; all P<0.001) inflammation. CXCL10:Cr diagnosed TCMR (area under the curve [AUC]=0.80; 95% confidence interval [95% CI], 0.68 to 0.92; P<0.001) and ABMR (AUC=0.76; 95% CI, 0.69 to 0.82; P<0.001) with high accuracy, even in the absence of tubulointerstitial inflammation (AUC=0.70; 95% CI, 0.61 to 0.79; P<0.001). Although mean fluorescence intensity of the immunodominant DSA diagnosed ABMR (AUC=0.75; 95% CI, 0.68 to 0.82; P<0.001), combining urinary CXCL10:Cr with immunodominant DSA levels improved the diagnosis of ABMR (AUC=0.83; 95% CI, 0.77 to 0.89; P<0.001). At the time of ABMR, urinary CXCL10:Cr ratio was independently associated with an increased risk of graft loss. In conclusion, urinary CXCL10:Cr ratio associates with tubulointerstitial and microvascular inflammation of the renal allograft. Combining the urinary CXCL10:Cr ratio with DSA monitoring significantly improves the noninvasive diagnosis of ABMR and the stratification of patients at high risk for graft loss.     

Proteinuria as a Noninvasive Marker for Renal Allograft Histology and Failure: An Observational Cohort Study

Proteinuria is routinely measured to assess renal allograft status, but the diagnostic and prognostic values of this measurement for renal transplant pathology and outcome remain unclear. We included 1518 renal allograft recipients in this prospective, observational cohort study. All renal allograft biopsy samples with concomitant data on 24-hour proteinuria were included in the analyses (n=2274). Patients were followed for ≥7 years post-transplantation. Compared with proteinuria <0.3 g/24 h, the hazard ratios for graft failure were 1.14 (95% confidence interval [95% CI], 0.81 to 1.60; P=0.50), for proteinuria 0.3–1.0 g/24 h, 2.17 (95% CI, 1.49 to 3.18; P<0.001), for proteinuria 1.0–3.0 g/24 h, and 3.01 (95% CI, 1.75 to 5.18; P<0.001), for proteinuria >3.0 g/24 h, independent of GFR and allograft histology. The predictive performance of proteinuria for graft failure was lower at 3 months after transplant (area under the receiver-operating characteristic curve [AUC] 0.64, P<0.001) than at 1, 2, and 5 years after transplant (AUC 0.73, 0.71, and 0.77, respectively, all P<0.001). Independent determinants of proteinuria were repeat transplantation, mean arterial pressure, transplant glomerulopathy, microcirculation inflammation, and de novo/recurrent glomerular disease. The discriminatory power of proteinuria for these intragraft injury processes was better in biopsy samples obtained >3 months after transplant (AUC 0.73, P<0.001) than in those obtained earlier (AUC 0.56, P<0.01), with 85% specificity but lower sensitivity (47.8%) for proteinuria >1.0 g/24 h. These data support current clinical guidelines to routinely measure proteinuria after transplant, but illustrate the need for more sensitive biomarkers of allograft injury and prognosis.     

Altered kidney function induced by SARS-CoV-2 infection and acute kidney damage markers predict survival outcomes of COVID-19 patients: a prospective pilot study

BackgroundLiterature with regard to coronavirus disease 2019 (COVID-19) associated morbidities and the risk factors for death are still emerging. In this study, we investigated the presence of kidney damage markers and their predictive value for survival among hospitalized subjects with COVID-19.MethodsForty-seven participants was included and grouped as: ‘COVID-19 patients before treatment’, ‘COVID-19 patients after treatment’, ‘COVID-19 patients under treatment in intensive care unit (ICU)’, and ‘controls’. Kidney function tests and several kidney injury biomarkers were compared between the groups. Cumulative rates of death from COVID-19 were determined using the Kaplan–Meier method. The associations between covariates including kidney injury markers and death from COVID-19 were examined, as well.ResultsSerum creatinine and cystatin C levels, urine Kidney Injury Molecule-1 (KIM-1)/creatinine ratio, and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), CKD-EPI cystatin C, and CKD-EPI creatinine–cystatin C levels demonstrated significant difference among the groups. The most significant difference was noted between the groups ‘COVID-19 patients before treatment’ and ‘COVID-19 patients under treatment in ICU’. Advancing age, proteinuria, elevated serum cystatin C, and urine KIM-1/creatinine ratio were all significant univariate correlates of death (p < 0.05, for all). However, only elevated urine KIM-1/creatinine ratio retained significance in an age, sex, and comorbidities adjusted multivariable Cox regression (OR 6.11; 95% CI: 1.22–30.53; p = 0.02), whereas serum cystatin C showing only a statistically non-significant trend (OR 1.42; 95% CI: 0.00–2.52; p = 0.09).ConclusionsOur findings clearly demonstrated the acute kidney injury related to COVID-19. Moreover, urine KIM-1/creatinine ratio was associated with COVID-19 specific death.     

Diagnostic value of TWEAK for predicting active lupus nephritis in patients with systemic lupus erythematosus: a systematic review and meta-analysis

Purpose Accumulative studies showed that tumor necrosis factor (TNF)-like weak inducer of apoptosis (TWEAK) was up-regulated in the blood and urine from patients diagnosed with lupus nephritis (LN) and that it might be used as a novel biomarker for active LN. This meta-analysis aimed to determine the diagnostic value of TWEAK in active LN.Methods We searched the Cochrane Library, Embase, PubMed, Springer, Wanfang and CNKI databases for articles published up to 20 August 2020. The diagnostic capacity of TWEAK for active LN was assessed using pooled sensitivity and specificity, positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratio (DOR), and area under the receiver operating characteristic curve (AUC). Quality assessment and publication bias were also evaluated. STATA 11.0 and Meta-Disc 1.4 were used to perform these analyses.Results Nine cross-sectional studies were included in this meta-analysis. The overall pooled sensitivity of TWEAK for the diagnosis of active LN was 0.69 (95% CI, 0.63–0.75), and specificity was 0.77 (95% CI, 0.71–0.82). The overall pooled PLR and NLR were 3.31 (95% CI, 2.05–5.35) and 0.38 (95% CI, 0.26–0.55), respectively, with a DOR of 10.89 (95% CI, 6.73–17.63) and AUC (SE) of 0.8276 (0.0289). Deeks’ funnel plot revealed that the publication bias was insignificant in the study (p = .32).Conclusions Our results suggest that TWEAK might be a potential biomarker for patients with active LN. Future cross-sectional and longitudinal studies are needed to confirm its diagnostic value, as well as to establish more definite cutoff for active LN.     

Flow cytometry crossmatching to investigate kidney-biopsy-proven,antibody-mediated rejection in patients who develop de novo donor-specific antibodies

IntroductionThe appearance of de novo donor-specific anti-human leukocyte antigen antibodies (dnDSAs) after kidney transplantation is independently associated with poor long-term allograft outcomes. The objective of the present study was to evaluate the predictive value of a flow cytometry crossmatching (FC-XM) assay after the appearance of dnDSAs related to antibody-mediated allograft rejection (ABMR) after kidney transplantation.Materials and methodsA total of 89 recipients with dnDSAs after transplantation were included. The crossmatching results were compared with the dnDSA profile (the mean fluorescence intensity (MFI), the complement-binding activity, and the IgG subclass profile) and the biopsy's morphological features.ResultsOf the 89 patients, 59 (66%) were positive in an FC-XM assay, 17 (19%) had complement-binding DSAs, 55 (62%) were positive for IgG1 and/or IgG3 in a solid phase assay, and 45 (51%) had morphological biopsy features linked to ABMR.ConclusionAn FC-XM assay was unable to discriminate between cases with or without ABMR on biopsy findings; it had a low positive predictive value (<70%) and a low negative positive predictive value (<42.9%), taking into account the sensitivity of our assay (limit of detection: DSAs with an MFI >3000). In this context, the height of the MFI of the dnDSAs might be enough for a high positive predictive value for ABMR and additional testing for complement binding activity can remain optional.     

Early clinical experience using donor‐derived cell‐free DNA to detect rejection in kidney transplant recipients

Donor‐derived cell‐free DNA (dd‐cfDNA) became Medicare reimbursable in the United States in October 2017 for the detection of rejection in kidney transplant recipients based on results from its pivotal validation trial, but it has not yet been externally validated. We assessed 63 adult kidney transplant recipients with suspicion of rejection with dd‐cfDNA and allograft biopsy. Of these, 27 (43%) patients had donor–specific antibodies and 34 (54%) were found to have rejection by biopsy. The percentage of dd‐cfDNA was higher among patients with antibody–mediated rejection (ABMR; median 1.35%; interquartile range [IQR]: 1.10%‐1.90%) compared to those with no rejection (median 0.38%, IQR: 0.26%‐1.10%; P < .001) and cell–mediated rejection (CMR; median: 0.27%, IQR: 0.19%‐1.30%; P = .01). The dd‐cfDNA test did not discriminate patients with CMR from those without rejection. The area under the ROC curve (AUC) for CMR was 0.42 (95% CI: 0.17‐0.66). For ABMR, the AUC was 0.82 (95% CI: 0.71‐0.93) and a dd‐cfDNA ≥0.74% yielded a sensitivity of 100%, specificity 71.8%, PPV 68.6%, and NPV 100%. The dd‐cfDNA test did not discriminate CMR from no rejection among kidney transplant recipients, although performance characteristics were stronger for the discrimination of ABMR.     

Polyomavirus polymerase chain reaction as a surrogate marker of polyomavirus-associated nephropathy

BACKGROUND: Polyomavirus-associated nephropathy (PVAN) is a significant cause of allograft loss after renal transplantation. A noninvasive assay that can guide the evaluation of PVAN would be of clinical value. We compared the utility of BK virus (BKV) polymerase chain reaction (PCR) and urine cytology in screening for concurrent PVAN. METHODS: We used PCR to test urine and plasma samples from renal recipients simultaneously for BKV DNA. Additionally, we tested urine samples for decoy cells. Sample results were correlated with biopsy-proven PVAN. Receiver-operator characteristic curves were used to determine viral load thresholds associated with concurrent PVAN. RESULTS: In this cross-sectional study, BKV viruria, viremia, and urinary decoy cells were detected in 24%, 9%, and 13% of renal recipients, respectively. Among 114 patients who had renal allograft biopsy, four (3.5%) were diagnosed with PVAN. Using pathology as gold standard for the diagnosis of PVAN, BKV viremia threshold of >1.6E+04 copies/mL had 100% sensitivity, 96% specificity, 50% positive predictive value, and 100% negative predictive value. A BKV viruria threshold of >2.5E+07 copies/mL had 100% sensitivity, 92% specificity, 31% positive predictive value, and 100% negative predictive value. In contrast, urine decoy cells had 25% sensitivity, 84% specificity, 5% positive predictive value, and 97% negative predictive value for the diagnosis of concurrent PVAN. CONCLUSION: BKV PCR may be a clinically useful noninvasive test to identify renal recipients with concurrent PVAN. BKV DNA >1.6E+04 copies/mL of plasma and >2.5E+07 copies/mL of urine were highly associated with concurrent PVAN whereas a negative PCR test makes the diagnosis of PVAN highly unlikely.     

Incorporation of Donor-derived Cell-free DNA Into Clinical Practice for Renal Allograft Management

BackgroundDonor-derived cell-free DNA (dd-cfDNA) in plasma is an established noninvasive biomarker for allograft injury and rejection. A single-nucleotide polymorphism (SNP)–based massively multiplexed polymerase chain reaction methodology can be used to quantify dd-cfDNA in kidney transplant recipients. In this study we describe our clinical experience in using a SNP-based dd-cfDNA assay for the management of active rejection in renal transplant recipients.MethodsTo assess the clinical utility of a clinically available SNP-based massively multiplexed polymerase chain reaction dd-cfDNA assay, we analyzed biopsy data contemporaneous to dd-cfDNA results at 33 participating clinics and calculated the rate of rejection in dd-cfDNA-matched biopsy results.ResultsA total of 1347 dd-cfDNA test samples from 879 patients were accessioned from October 3, 2019, to November 2, 2020. The dd-cfDNA testing classified 25.2% (340/1347) of samples as high-risk (dd-cfDNA fraction ≥ 1%). Clinical follow-up was available for 32.1% (109/340) of the high-risk results, which included samples from 28 patients with definitive biopsy results within 2 weeks of dd-cfDNA testing. Pathology reports indicated a 64% (18/28) rate of active rejection in biopsy result–matched samples. Total cfDNA measurements indicated a skewed distribution and a correlation with dd-cfDNA-derived patient risk classification.ConclusionsThis is the first report showing the impact of dd-cfDNA on patient management in a multicenter real-world clinical cohort. The data indicate that incorporating dd-cfDNA testing into practice may improve physician decision making regarding renal allograft recipients.     

Isolated Endarteritis and Kidney Transplant Survival: A Multicenter Collaborative Study

Isolated endarteritis of kidney transplants is increasingly recognized. Notably, microarray studies revealed absence of immunologic signatures of rejection in most isolated endarteritis biopsy samples. We investigated if isolated endarteritis responds to rejection treatment and affects kidney transplant survival. We retrospectively enrolled recipients of kidney transplant who underwent biopsies between 1999 and 2011 at seven American and Canadian centers. Exclusion criteria were recipients were blood group-incompatible or crossmatch-positive or had C4d-positive biopsy samples. After biopsy confirmation, patients were divided into three groups: isolated endarteritis (n=103), positive controls (type I acute T cell-mediated rejection with endarteritis; n=101), and negative controls (no diagnostic rejection; n=103). Primary end points were improved kidney function after rejection treatment and transplant failure. Mean decrease in serum creatinine from biopsy to 1 month after rejection treatment was 132.6 µmol/L (95% confidence interval [95% CI], 78.7 to 186.5) in patients with isolated endarteritis, 96.4 µmol/L (95% CI, 48.6 to 143.2) in positive controls (P=0.32), and 18.6 µmol/L (95% CI, 1.8 to 35.4) in untreated negative controls (P<0.001). Functional improvement after rejection treatment occurred in 80% of patients with isolated endarteritis and 81% of positive controls (P=0.72). Over the median 3.2-year follow-up period, kidney transplant survival rates were 79% in patients with isolated endarteritis, 79% in positive controls, and 91% in negative controls (P=0.01). In multivariate analysis, isolated endarteritis was associated with an adjusted 3.51-fold (95% CI, 1.16 to 10.67; P=0.03) risk for transplant failure. These data indicate that isolated endarteritis is an independent risk factor for kidney transplant failure.