John R. Lee

Independent Risk Factors for Urinary Tract Infection and for Subsequent Bacteremia or Acute Cellular Rejection: A Single Center Report of 1166 Kidney Allograft Recipients

Background Urinary tract infection (UTI) is a frequent, serious complication in kidney allograft recipients. Methods We reviewed the records of 1166 kidney allograft recipients who received their allografts at our institution between January 2005 and December 2010 and determined the incidence of UTI during the first 3 months after transplantation (early UTI). We used Cox proportional hazards models to determine the risk factors for early UTI and whether early UTI was an independent risk factor for subsequent bacteremia or acute cellular rejection (ACR). Results UTI, defined as 105 or more bacterial colony-forming units/mL urine, developed in 247 (21%) of the 1166 recipients. Independent risk factors for the first episode of UTI were female gender (hazard ratio [HR], 2.9; 95% confidence intervals [CI], 2.2–3.7; P<0.001), prolonged use of Foley catheter (HR, 3.9; 95% CI, 2.8–5.4; P <0.001), ureteral stent (HR, 1.4; 95% CI, 1.1–1.8; P=0.01), age (HR, 1.1; 95% CI, 1.0–1.2; P=0.03), and delayed graft function (HR, 1.4; 95% CI, 1.0–1.9; P=0.06). Trimethoprim/sulfamethoxazole prophylaxis was associated with a reduced risk of UTI (HR, 0.6; 95% CI, 0.3–0.9; P=0.02). UTI was an independent risk factor for subsequent bacteremia (HR, 2.4; 95% CI, 1.2–4.8; P=0.01). Untreated UTI, but not treated UTI, was associated with an increased risk of ACR (HR, 2.8; 95% CI, 1.3–6.2; P=0.01). Conclusions Female gender, prolonged use of Foley catheter, ureteral stent, age, and delayed graft function are independent risk factors for early UTI. UTI is independently associated with the development of bacteremia, and untreated UTI is associated with subsequent ACR.

Gut microbial community structure and complications after kidney transplantation: a pilot study.

Background The gut microbiome plays a role in the regulation of the immune system. Methods We prospectively enrolled 26 kidney transplant recipients and collected serial fecal specimens (N=85) during the first three months of transplantation. We characterized bacterial composition by polymerase chain reaction amplification of the 16S rRNA V4-V5 variable region and deep sequencing using the Illumina MiSeq platform. Results An increase in the relative abundance of Proteobacteria was observed in the posttransplantation specimens compared to pretransplantation specimens (P=0.04, Wilcoxon signed-rank test). In patients with posttransplant diarrhea, the mean(±standard deviation [SD]) Shannon diversity index was lower in those with diarrhea (N=6) than those without diarrhea (N=9) (2.5±0.3 vs. 3.4±0.8; P = 0.02, Wilcoxon rank-sum test). Principal coordinate analysis showed clear separation between the two groups, and linear discriminant analysis effect size (LEfSe) method revealed that Bacteroides, Ruminococcus, Coprococcus, and Dorea were significantly lower in the patients with diarrhea. Principal coordinate analysis also showed clear separation between the acute rejection (AR) group (N=3) and the no AR group (N=23) and the LEfSe method revealed significant differences between the two groups. Fecal abundance of Enterococcus was associated with Enterococcus urinary tract infection (UTI). The median Enterococcus fecal abundance was 24% (range, 8%–95%) in the three patients with Enterococcus UTI compared to 0% in the 23 patients without Enterococcus UTI (interquartile range, 0.00%–0.08%) (P=0.005, Wilcoxon rank-sum test). Conclusion Our pilot study identified significant alterations in the gut microbiota after kidney transplantation. Moreover, distinct microbiota structures were observed in allograft recipients with posttransplant diarrhea, AR, and Enterococcus UTI.

Gut Microbiota and Tacrolimus Dosing in Kidney Transplantation

Tacrolimus dosing to establish therapeutic levels in recipients of organ transplants is a challenging task because of much interpatient and intrapatient variability in drug absorption, metabolism, and disposition. In view of the reported impact of gut microbial species on drug metabolism, we investigated the relationship between the gut microbiota and tacrolimus dosing requirements in this pilot study of adult kidney transplant recipients. Serial fecal specimens were collected during the first month of transplantation from 19 kidney transplant recipients who either required a 50% increase from initial tacrolimus dosing during the first month of transplantation (Dose Escalation Group, n=5) or did not require such an increase (Dose Stable Group, n=14). We characterized bacterial composition in the fecal specimens by deep sequencing of the PCR amplified 16S rRNA V4-V5 region and we investigated the hypothesis that gut microbial composition is associated with tacrolimus dosing requirements. Initial tacrolimus dosing was similar in the Dose Escalation Group and in the Stable Group (4.2±1.1 mg/day vs. 3.8±0.8 mg/day, respectively, P=0.61, two-way between-group ANOVA using contrasts) but became higher in the Dose Escalation Group than in the Dose Stable Group by the end of the first transplantation month (9.6±2.4 mg/day vs. 3.3±1.5 mg/day, respectively, P<0.001). Our systematic characterization of the gut microbial composition identified that fecal Faecalibacterium prausnitzii abundance in the first week of transplantation was 11.8% in the Dose Escalation Group and 0.8% in the Dose Stable Group (P=0.002, Wilcoxon Rank Sum test, P<0.05 after Benjamini-Hochberg correction for multiple hypotheses). Fecal Faecalibacterium prausnitzii abundance in the first week of transplantation was positively correlated with future tacrolimus dosing at 1 month (R=0.57, P=0.01) and had a coefficient±standard error of 1.0±0.6 (P=0.08) after multivariable linear regression. Our novel observations may help further explain inter-individual differences in tacrolimus dosing to achieve therapeutic levels.

Circulating Levels of 25-Hydroxyvitamin D and Acute Cellular Rejection in Kidney Allograft Recipients

Background Vitamin D, in addition to its established role in bone metabolism, may regulate the immune system and affect the outcome of allografts. Methods We identified 351 kidney allograft recipients who had serum levels of 25-hydroxyvitamin D (25[OH]D) measured within the first 30 days of transplantation. We evaluated the relationship between the circulating levels of 25(OH)D and acute cellular rejection (ACR), cytomegalovirus (CMV) disease, BK virus nephropathy, and kidney graft function. Results Vitamin D deficiency (circulating levels of 25[OH]D ⩽20 ng/mL, defined using The Endocrine Society Clinical Practice 2011 Guideline) was observed in 216 (61.5%) of 351 kidney graft recipients. Vitamin D deficiency was more frequent in female recipients (P=0.007, Fisher exact test) and African American recipients (P<0.001) and was less frequent in preemptive kidney graft recipients (P=0.002). Biopsy-confirmed ACR was more frequent in the vitamin D–deficient group than in the sufficient group (10.2% vs. 3.7%, P=0.04). By multivariable Cox regression analysis, vitamin D deficiency was an independent risk factor for ACR (hazard ratio=3.3, P=0.02). Vitamin D deficiency was not associated with CMV disease, BK virus nephropathy, or kidney allograft function at 1 year. 1,25-Dihydroxyvitamin D3 supplementation initiated within the first 90 days of transplantation was associated with a lesser incidence of ACR compared to no treatment with 1,25-dihydroxyvitamin D3 (5.1% vs. 13.0%, P=0.099). Conclusions Vitamin D deficiency is an independent risk factor for development of ACR within the first year of kidney transplantation and 1,25-dihydroxyvitamin D3 supplementation may help reduce the occurrence of ACR in the vitamin D–deficient group.

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 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).

Characteristics of Circulating Donor Human Leukocyte Antigen-specific Immunoglobulin G Antibodies Predictive of Acute Antibody-mediated Rejection and Kidney Allograft Failure.

Background Characteristics of pretransplant antibodies directed at donor human leukocyte antigen (HLA) donor-specific antibodies (DSA) associated with adverse outcomes in kidney transplant recipients are being elucidated but uncertainties exist. Methods We prospectively screened pretransplant sera from 543 kidney recipients using single antigen bead assays and identified 154 patients with and 389 without DSA. We investigated the association of DSA features to acute rejection and graft failure. Results One-year acute rejection incidence was higher in DSA-positive group (P < 0.001), primarily due to antibody-mediated rejection (AMR, 13% vs. 1.8%, P < 0.001) and not T cell–mediated rejection (ACR, 5% vs.6%, P = 0.65). The sum of mean fluorescence intensity of DSA (DSA MFI-Sum) of 6,000 or higher (OR, 18; 95% CI, 7.0–47; P < 0.001) and the presence of DSA against both HLA class I and II (OR, 39; 95% CI, 14–106; P < 0.0001) predicted 1-year AMR, independent of other covariates. Calculated panel reactive antibody and a positive flow cytometry cross-match result were associated with AMR by bivariate analysis but neither was an independent predictor in a multivariable regression analysis that included DSA-MFI-Sum or HLA DSA class. In multivariable Cox proportional hazards models, the covariate-adjusted hazard ratio for graft failure was 2.03 (95%CI, 1.05–3.92; P = 0.04) for DSA MFI-Sum of 6,000 or higher and 2.23 (95% CI, 1.04–4.80; P = 0.04) for class I and II DSA. Prediction of graft failure was not independent of AMR. Conclusion Our study suggests that DSA MFI-Sum and HLA class of DSA are characteristics predictive of AMR and graft failure. The elevated risk of graft failure in those with the identified features of DSA is attributable to increased risk of AMR.

Epidemiology and outcomes of carbapenem-resistant Klebsiella pneumoniae bacteriuria in kidney transplant recipients

Little is known about the epidemiology of carbapenem‐resistant Klebsiella pneumoniae (CRKP) bacteriuria following kidney transplantation. We determined the incidence of post‐transplant CRKP bacteriuria in adults who underwent kidney transplant from 2007 to 2010 at 2 New York City centers.

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.

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<0.001) by receiver operating characteristic curve analysis, and the area under the curve was 0.92 (95% CI, 0.80–1.0; P<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.