Allograft rejection and tubulointerstitial fibrosis in human kidney allografts: Interrogation by urinary cell mRNA profiling

Because the kidney allograft has the potential to function as an in-vivo flow cytometer and facilitate the access of immune cells and kidney parenchymal cells in to the urinary space, we hypothesized that mRNA profiling of urinary cells offers a noninvasive means of assessing the kidney allograft status. We overcame the inherent challenges of urinary cell mRNA profiling by developing pre-amplification protocols to compensate for low RNA yield from urinary cells and by developing robust protocols for absolute quantification mRNAs using RT-PCR assays. Armed with these tools, we undertook first single-center studies urinary cell mRNA profiling and then embarked on the multicenter Clinical Trials in Organ Transplantation-04 study of kidney transplant recipients. We report here our discovery and validation of diagnostic and prognostic biomarkers of acute cellular rejection and of interstitial fibrosis and tubular atrophy (IF/TA). Our urinary cell mRNA profiling studies, in addition to demonstrating the feasibility of accurate diagnosis of acute cellular rejection and IF/TA in the kidney allograft, advance mechanistic and potentially targetable biomarkers. Interventional trials, guided by urinary cell mRNA profiles, may lead to personalized immunosuppression in recipients of kidney allografts

Urinary cell mRNA profiles predictive of human kidney allograft status

Kidney allograft status is currently characterized using the invasive percutaneous needle core biopsy procedure. The procedure has become safer over the years, but challenges and complications still exist including sampling error, interobserver variability, bleeding, arteriovenous fistula, graft loss, and even death. Because the most common type of acute rejection is distinguished by inflammatory cells exiting the intravascular compartment and gaining access to the renal tubular space, we reasoned that a kidney allograft may function as an in vivo flow cytometer and sort cells involved in rejection into urine. To test this idea, we developed quantitative polymerase chain reaction (PCR) assays for absolute quantification of mRNA and pre-amplification protocols to overcome the low RNA yield from urine. Here, we review our single center urinary cell mRNA profiling studies that led to the multicenter Clinical Trials in Organ Transplantation (CTOT-04) study and the discovery and validation of a 3-gene signature of 18S rRNA-normalized measures of CD3ε mRNA and IP-10 mRNA and 18S rRNA that is diagnostic and predictive of acute cellular rejection in the kidney allograft. We also review our development of a 4-gene signature of mRNAs for vimentin, NKCC2, E-cadherin, and 18S rRNA diagnostic of interstitial fibrosis/tubular atrophy (IF/TA)

Urinary-Cell mRNA Profile and Acute Cellular Rejection in Kidney Allografts

Background—The standard test for the diagnosis of acute rejection in kidney transplants is the renal biopsy. Noninvasive tests would be preferable. Methods—We prospectively collected 4300 urine specimens from 485 kidney-graft recipients from day 3 through month 12 after transplantation. Messenger RNA (mRNA) levels were measured in urinary cells and correlated with allograft-rejection status with the use of logistic regression. Results—A three-gene signature of 18S ribosomal (rRNA)–normalized measures of CD3ε mRNA and interferon-inducible protein 10 (IP-10) mRNA, and 18S rRNA discriminated between biopsy specimens showing acute cellular rejection and those not showing rejection (area under the curve [AUC], 0.85; 95% confidence interval [CI], 0.78 to 0.91; P<0.001 by receiver-operatingcharacteristic curve analysis). The cross-validation estimate of the AUC was 0.83 by bootstrap resampling, and the Hosmer–Lemeshow test indicated good fit (P = 0.77). In an externalvalidation data set, the AUC was 0.74 (95% CI, 0.61 to 0.86; P<0.001) and did not differ significantly from the AUC in our primary data set (P = 0.13). The signature distinguished acute cellular rejection from acute antibody-mediated rejection and borderline rejection (AUC, 0.78; 95% CI, 0.68 to 0.89; P<0.001). It also distinguished patients who received anti–interleukin-2 receptor antibodies from those who received T-cell–depleting antibodies (P<0.001) and was diagnostic of acute cellular rejection in both groups. Urinary tract infection did not affect the signature (P = 0.69). The average trajectory of the signature in repeated urine samples remained below the diagnostic threshold for acute cellular rejection in the group of patients with no rejection, but in the group with rejection, there was a sharp rise during the weeks before the biopsy showing rejection (P<0.001). Conclusions—A molecular signature of CD3ε mRNA, IP-10 mRNA, and 18S rRNA levels in urinary cells appears to be diagnostic and prognostic of acute cellular rejection in kidney allografts

Noninvasive prognostication of polyomavirus BK virus-associated nephropathy.

BACKGROUND: BK virus-associated nephropathy (BKVN) is associated with an increased risk of graft failure. METHODS: Levels of mRNAs encoding proteins implicated in inflammation and fibrosis were measured in urine collected at the time of biopsy diagnosis of BKVN in 29 kidney graft recipients and analyzed for prognosticating graft failure using logistic regression. RESULTS: Ten of 29 BKVN patients had graft failure within 36 months of BKVN diagnosis and the remaining 19 patients did not. Serum creatinine level, BKVN biopsy stage, and urinary cell levels of mRNA for plasminogen activator inhibitor (PAI)-1, vimentin, tissue inhibitor of metalloproteinase-1, fibronectin, granzyme B, or perforin were associated with graft failure. A combination of PAI-1 mRNA level, BKVN biopsy stage, and creatinine level (P = 0.0015, by logistic regression) and a combination of PAI-1 mRNA and creatinine levels (P = 0.001) were the best-fitting models for prognosticating graft failure, and PAI-1 mRNA level was the only independent predictor (odds ratio, 2.8; 95% confidence interval [CI], 1.1-6.8; P = 0.03) by multivariable analysis. The area under the curve for the combination of PAI-1 mRNA, biopsy, and creatinine was 0.92 (95% CI, 0.80-1.0; P &lt; 0.001) by receiver operating characteristic curve analysis, and the area under the curve was 0.92 (95% CI, 0.80-1.0; P &lt; 0.001) for the combination of PAI-1 mRNA and creatinine. Graft outcome was correctly predicted in 27 of 29 BKVN patients by either model. CONCLUSION: Urinary cell level of PAI-1 mRNA, measured at the time of BKVN diagnosis, is an independent prognosticator of graft failure and a prediction model of serum creatinine and PAI-1 mRNA is as accurate as the model that includes the biopsy result