Background The CYP4503A5*1 genotype is associated with lower tacrolimus concentrations. Although its effect is important, it incompletely explains the variability in tacrolimus concentrations and has a relatively low minor allele frequency in Caucasians relative to African Americans (AA). Methods We studied clinical and recipient genetic correlates of dose-normalized tacrolimus troughs (n=12,277) in the first 6 months posttransplant using a customized single nucleotide polymorphism chip with 2,722 variants in a large, ethnically diverse (144 AA and 551 non-AA) adult kidney transplant population through a 7-center consortium. Results Over the 6 month study, AAs had consistently lower median (interquartile range) troughs than non-AAs, 6.2 (4.4–8.4) vs 8.3 (6.4–10.4) ng/mL (p<0.0001), in spite of 60% higher daily doses, 8 (5–10) vs 5 (4–7) mg (p<0.0001). The median tacrolimus trough concentration in week one posttransplant was particularly low in AAs [2.1 (1.2–3.5)] compared to non-AAs [5.0 (3.1–8.2) ng/mL](p<0.0001) despite similar initial doses. In single variant analysis, CYP3A5*3 (rs776746) was the top variant (p=2.4x10−33) associated with troughs. After adjustment for CYP3A5*3, clinical factors and race, thirty-nine additional variants were identified (p<0.01, not significant at FDR 20%). In the final multivariant, regression models beginning with these variants and clinical factors, 7 variants were identified in the non-AA and 7 variants in the AA group towards the first trough concentrations. Rs776746 (CYP3A5), rs2239393 (COMT) and diabetes were the only factors common in both populations. Conclusion We identified variants beyond CYP3A5*3 which may further explain pharmacokinetic variability of tacrolimus and demonstrated that important variants differ by race.

We are studying two cohorts of kidney transplant recipients, with the goal of defining specific clinicopathologic entities that cause late graft dysfunction: (1) prevalent patients with new onset late graft dysfunction (Cross-Sectional Cohort); and (2) newly transplanted patients (Prospective Cohort). For the cross-sectional cohort (n=440), mean time from transplant to biopsy was 7.5±6.1 years. Local pathology diagnoses included CAN (48%), CNI toxicity (30%), and, perhaps surprisingly, acute rejection (cellular- or Ab-mediated) (23%). Actuarial rate of death-censored graft loss at 1 year post-biopsy was 17.7%; at 2 years, 29.8%. There was no difference in post-biopsy graft survival for recipients with vs. without CAN (p=0.9). Prospective cohort patients (n=2427) developing graft dysfunction >3 months posttransplant undergo “index” biopsy. The rate of index biopsy was 8.8% between months 3 and 12, and 18.2% by 2 years. Mean time from transplant to index biopsy was 1.0 ± 0.6 years. Local pathology diagnoses included CAN (27%), and acute rejection (39%). Intervention to halt late graft deterioration cannot be developed in the absence of meaningful diagnostic entities. We found CAN in late posttransplant biopsies to be of no prognostic value. The DeKAF study will provide broadly applicable diagnostic information to serve as the basis for future trials.

Tacrolimus is dependent on CYP3A5 enzyme for metabolism. Expression of the CYP3A5 enzyme is controlled by several alleles including CYP3A5*1, CYP3A5*3, CYP3A5*6 and CYP3A5*7. African Americans (AA) have on average higher tacrolimus dose requirements than Caucasians; however, some have requirements similar to Caucasians. Studies in AA have primarily evaluated the CYP3A5*3 variant; however, there are common nonfunctional variants in AA (CYP3A5*6 and CYP3A5*7) which do not occur in Caucasians. These variants are associated with lower dose requirements and may explain why some AA are metabolically similar to Caucasians. We created a tacrolimus clearance model in 354 AA using a development and validation cohort. Time posttransplant, steroid and antiviral use, age, CYP3A5*1, *3, *6 and *7 alleles were significant towards clearance. This study is the first to develop an AA specific genotype-guided tacrolimus dosing model to personalize therapy.

Clostridium difficile infection (CDI) is a considerable health issue in the United States, and represents the most common healthcare-associated infection. Solid organ transplant recipients are at increased risk of CDI, which can impact graft as well as patient survival. However, little is known about the impact of CDI on health services utilization post-transplant. We examined hospital-onset CDI from 2012-2014 among transplant recipients in the University HealthSystem Consortium, which includes academic medical center-affiliated hospitals in the US. Infection was five times more common among transplant recipients compared to general inpatients (209 vs. 40 per 10,000 discharges) and factors associated with CDI among transplant recipients included transplant type, risk of mortality, comorbidities, and inpatient complications. Institutional risk-standardized CDI varied more than three-fold across high-volume hospitals (infection ratio 0.54-1.82; median 1.04; interquartile range 0.78-1.28). CDI was associated with increased 30-day readmission, transplant organ complications and cytomegalovirus infection, inpatient costs, and lengths of stay. Total observed inpatient days and direct costs for those with CDI were substantially higher than risk-standardized expected values (40,094 vs. 22,843 days; $198,728,368 vs. $154,020,528 costs). Further efforts to detect, prevent, and manage CDI among solid organ transplant recipients are warranted.

A serum proteomics platform enabling expression Profiling in transplantation-associated clinical subsets gives an opportunity to identify non-invasive biomarkers that can accurately predict transplant outcome. In this study, we attempted to identify candidate serum biomarkers that could predict kidney allograft rejection/injury, regardless of its etiological and therapeutic heterogeneity. Using serum samples collected from kidney transplantation patients and healthy controls, we first employed Clontech-500 Ab microarrays to Profile acute rejection (AR) and chronic graft injury (CGI) versus stable graft function (SF) and normal kidneys (NK). Using GenePattern analysis of duplicate arrays on pooled samples, we identified gender-independent biomarkers PARP1, MAPK1, SRP54, DP1, and p57 (FDR ≈ 25%), the concordant downregulation of which represented a detrimental Profile common for both rejection/ injury types (AR-CGI). The reverse phase arrays qualified a 2-fold upregulation of PARP1 with an ROC of 0.87 in individual samples from patients with SF vs. AR-CGI rendering serum PARP1 as a biomarker for early prognosis. Ingenuity Pathways Analysis (IPA) connected PARP1 to some other markers (MAPK1), elucidating their possible interactions and connections to the immune response and graft-versus-host disease signaling. The downregulation of serum PARP1 in the damaged graft tissues, represents a perspective non-invasive marker, predicting the failing kidney graft, regardless of rejection/injury causes or gender. Thus, the successful identification of PARP1 as a bio-marker in limited patient cohorts demonstrates that serum proteomics platform empowered by the GenePattern- and IPA-based Bioinformatics algorithm can guarantee a successful development of the clinically applicable prognostic biomarker panel.