Recent studies have established that the human urine contains a complex microbiome, including a virome about which little is known. Following immunosuppression in kidney transplant patients, BK polyomavirus (BKV) has been shown to induce nephropathy (BKVN), decreasing graft survival. In this study we investigated the urine virome profile of BKV+ and BKV− kidney transplant recipients. Virus-like particles were stained to confirm the presence of VLP in the urine samples. Metagenomic DNA was purified, and the virome profile was analyzed using metagenomic shotgun sequencing. While the BK virus was predominant in the BKV+ group, it was also found in the BKV− group patients. Additional viruses were also detected in all patients, notably including JC virus (JCV) and Torque teno virus (TTV) and interestingly, we detected multiple subtypes of the BKV, JCV and TTV. Analysis of the BKV subtypes showed that nucleotide polymorphisms were detected in the VP1, VP2 and Large T Antigen proteins, suggesting potential functional effects for enhanced pathogenicity. Our results demonstrate a complex urinary virome in kidney transplant patients with multiple viruses with several distinct subtypes warranting further analysis of virus subtypes in immunosuppressed hosts.
Recent studies have established that a complex community of microbes colonize the human urinary tract; however their role in kidney transplant patients treated with prophylactic antibiotics remains poorly investigated. Our aim was to investigate the urinary microbiome of kidney transplant recipients. Urine samples from 21 patients following kidney transplantation and 8 healthy controls, were collected. All patients received prophylactic treatment with the antibiotic trimethoprim/sulfamethoxazole. Metagenomic DNA was isolated from urine samples, sequenced using metagenomics shotgun sequencing approach on Illumina HiSeq2000 platform, and analyzed for microbial taxonomic and functional annotations. Our results demonstrate that the urine microbiome of kidney transplants was markedly different at all taxonomic levels from phyla to species, had decreased microbial diversity and increased abundance of potentially pathogenic species compared to healthy controls. Specifically, at the phylum level we detected a significant decrease in Actinobacteria and increase in Firmicutes due to increases in Enterococcus faecalis. In addition, there was an increase in the Proteobacteria due to increases in E. coli. Analysis of predicted functions of the urinary metagenome revealed increased abundance of enzymes in the folate pathway including dihydrofolate synthase that are not inhibited by trimethoprim/ sulfamethoxazole, but can augment folate metabolism. This report characterizes the urinary microbiome of kidney transplants using shotgun metagenomics approach. Our results indicate that the urinary microbiota may be modified in the context of prophylactic antibiotics, indicating that a therapeutic intervention may shift the urinary microbiota to select bacterial species with increased
BackgroundObesity is a growing epidemic in most developed countries including the United States resulting in an increased number of obese patients with end-stage renal disease. A previous study has shown that obese patients with end-stage renal disease have a survival benefit with transplantation compared with dialysis. However, due to serious comorbidities, many centers place restrictions on the selection of obese patients for transplantation. Further, due to obese patients having an increased risk of diabetes, it is unclear whether obesity can be an independent risk, independent of diabetes for increasing adverse renal transplant outcomes.MethodsTo investigate the role of obesity in kidney transplantation, we used the Scientific Registry of Transplant Recipients database. After filtering for subjects that had the full set of covariates including age, gender, graft type, ethnicity, diabetes, peripheral vascular disease, dialysis time and time period of transplantation for our analysis, 191,091 subjects were included in the analyses. Using multivariate logistic regression analyses adjusted for covariates we determined whether obesity is an independent risk factor for adverse outcomes such as delayed graft function, acute rejection, urine protein and graft failure. Cox regression modeling was used to determine hazard ratios of graft failure.ResultsUsing multivariate model analyses, we found that obese patients have significantly increased risk of adverse transplant outcomes, including delayed graft function, graft failure, urine protein and acute rejection. Cox regression modeling hazard ratios showed that obesity also increased risk of graft failure. Life-table survival curves showed that obesity may be a risk factor independent of diabetes mellitus for a shorter time to graft failure.ConclusionsA key observation in our study is that the risks for adverse outcome of obesity are progressive with increasing body mass index. Furthermore, pre-obese overweight recipients compared with normal weight recipients also had increased risks of adverse outcomes related to kidney transplantation.
Renal transplant outcomes have been shown to be impacted by ethnicity. Prior studies have evaluated the disparate transplant outcomes of Black recipients and recipients of Black donors. However, it has remained unclear whether other donor ethnicities independent of medical comorbidities can influence transplant outcomes. Utilizing the Scientific Registry of Transplant Recipients (SRTR) (with greater than 100,000 patients), we evaluated the effect of each ethnicity, Black, American Indian, Hispanic, Native Hawaiian or other Pacific Islander, and Asian as compared to White recipients on adverse kidney transplant outcomes, assessing for delayed graft function, positive urine protein, acute rejection, and graft failure. Additionally, we assessed the interplay of donor ethnicity on recipient transplant outcomes, which has not previously been comprehensively examined. Logistic regression analysis that took into consideration gender, age, comorbidities, graft type, donor ethnicity, body mass index (BMI), HLA mismatch, ever been on hemodialysis, and time on dialysis indicates that Black recipients have worse outcomes compared to Whites in all outcomes assessed. A logistic regression analysis showed that recipient ethnicity was an independent risk factor for adverse outcomes. Notably, we found that donor ethnicity also independently affects graft outcomes. Hispanic donors lead to better outcomes in Whites and Blacks, while Asian donors have the best outcomes amongst Asian recipients. Recipients of Black donors fared the worst of all ethnicity donors. These data suggest the potential importance of risk stratification for the donor allograft and developing risk calculators that include both donor and recipient ethnicity may be useful, which the current Kidney Donor Profile Index (KDPI) does not currently take into account as they give black donors a different weight, but the same score is assigned to Whites, Asians, and Hispanics.
Background. Tacrolimus demonstrates wide intrapatient and interpatient variability requiring therapeutic drug monitoring. The utility of tacrolimus time in therapeutic range (TTR) after renal transplantation (RT) under an early corticosteroid withdrawal (ECSWD) protocol is unknown. The purpose of this study is to assess the impact of tacrolimus TTR in an ECSWD RT population. Materials. A retrospective analysis of adult RT recipients maintained on tacrolimus was conducted. Patients were excluded if they were on nonstandard protocol immunosuppression agents <12 months post-RT. Tacrolimus TTR was calculated using the Rosendaal method. Patients were divided into high (TTR-H) and low (TTR-L) TTR groups based on cohort median. The primary outcome was to compare the incidence of acute rejection 12 months post-RT. Secondary outcomes included comparing rejection subtypes, incidence of donor-specific antibody (DSA) and de novo DSA (dnDSA), risk factors for acute rejection and dnDSA development, and allograft function (serum creatinine and estimated glomerular filtration rate). Results. A total of 193 patients were analyzed (TTR-H = 98 and TTR-L = 95). There was no difference in the incidence of acute rejection (TTR-H 20.4% versus TTR-L 20.0%; P = 0.944). Positive DSA posttransplant (odds ratio [OR], 3.62; 95% confidence interval [CI], 1.41-9.26; P = 0.007) was associated with a higher acute rejection at 12 months posttransplant. Mycophenolate dose reduction (OR, 2.82; 95% CI, 1.13-6.97; P = 0.025) and acute rejection (OR, 2.99; 95% CI, 1.09-8.18; P = 0.032) were associated with dnDSA formation. No difference in serum creatinine or estimated glomerular filtration rate was observed ( P > 0.05). Conclusions. Tacrolimus TTR was not significantly different with regards to acute rejection in an ECSWD population. Future studies are still needed to determine tacrolimus TTR thresholds post-RT and identify populations that may benefit from this intrapatient variability monitoring parameter.
Among kidney transplant recipients, the treatment of choice for acute T cell-mediated rejection (TCMR) with pulse steroids or antibody protocols has variable outcomes. Some rejection episodes are resistant to an initial steroid pulse, but respond to subsequent antibody protocols. The biological mechanisms causing the different therapeutic responses are not currently understood. Histological examination of the renal allograft is considered the gold standard in the diagnosis of acute rejection. The Banff Classification System was established to standardize the histopathological diagnosis and to direct therapy. Although widely used, it shows variability among pathologists and lacks criteria to guide precision individualized therapy. The analysis of the transcriptome in allograft biopsies, which we analyzed in this study, provides a strategy to develop molecular diagnoses that would have increased diagnostic precision and assist the development of individualized treatment. Our hypothesis is that the histological classification of TCMR contains multiple subtypes of rejection. Using R language algorithms to determine statistical significance, multidimensional scaling, and hierarchical, we analyzed differential gene expression based on microarray data from biopsies classified as TCMR. Next, we identified KEGG functions, protein–protein interaction networks, gene regulatory networks, and predicted therapeutic targets using the integrated database ConsesnsusPathDB (CPDB). Based on our analysis, two distinct clusters of biopsies termed TCMR01 and TCMR02 were identified. Despite having the same Banff classification, we identified 1933 differentially expressed genes between the two clusters. These genes were further divided into three major groups: a core group contained within both the TCMR01 and TCMR02 subtypes, as well as genes unique to TCMR01 or TCMR02. The subtypes of TCMR utilized different biological pathways, different regulatory networks and were predicted to respond to different therapeutic agents. Our results suggest approaches to identify more precise molecular diagnoses of TCMR, which could form the basis for personalized treatments.
Allograft rejection is a significant cause of renal transplant failure which needs prompt diagnosis and treatment for graft salvage. Angiotensin II type 1 receptor antibody-mediated rejection (AT1R-AMR) is increasingly being identified as the etiology of antibody-mediated rejection in kidney transplant recipients with allograft rejection but without detectable human leukocyte antigen (HLA) antibodies. While some reports have suggested that AT1R-AMR may be refractory to standard therapy, others have reported improvement or stabilization of graft function. We present two patients in which anti-rejection therapy including therapeutic plasma exchange was unable to salvage the allograft.
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