32 research outputs found
High prevalence of non-steroidal anti-inflammatory drug use among acute kidney injury survivors in the southern community cohort study
Design and implementation of the international genetics and translational research in transplantation network
Concept and design of a genome-wide association genotyping array tailored for transplantation-specific studies
High prevalence of non-steroidal anti-inflammatory drug use among acute kidney injury survivors in the southern community cohort study
UTILIZATION OF AN EMR-BIOREPOSITORY TO IDENTIFY THE GENETIC PREDICTORS OF CALCINEURIN-INHIBITOR TOXICITY IN HEART TRANSPLANT RECIPIENTS
Calcineurin-inhibitors CI are immunosuppressive agents prescribed to patients after solid organ transplant to prevent rejection. Although these drugs have been transformative for allograft survival, long-term use is complicated by side effects including nephrotoxicity. Given the narrow therapeutic index of CI, therapeutic drug monitoring is used to prevent acute rejection from underdosing and acute toxicity from overdosing, but drug monitoring does not alleviate long-term side effects. Patients on calcineurin-inhibitors for long periods almost universally experience declines in renal function, and a subpopulation of transplant recipients ultimately develop chronic kidney disease that may progress to end stage renal disease attributable to calcineurin inhibitor toxicity (CNIT). Pharmacogenomics has the potential to identify patients who are at high risk for developing advanced chronic kidney disease caused by CNIT and providing them with existing alternate immunosuppressive therapy. In this study we utilized BioVU, Vanderbilt University Medical Center's DNA biorepository linked to de-identified electronic medical records to identify a cohort of 115 heart transplant recipients prescribed calcineurin-inhibitors to identify genetic risk factors for CNIT We identified 37 cases of nephrotoxicity in our cohort, defining nephrotoxicity as a monthly median estimated glomerular filtration rate (eGFR) <30 mL/min/1.73m2 at least six months post-transplant for at least three consecutive months. All heart transplant patients were genotyped on the Illumina ADME Core Panel, a pharmacogenomic genotyping platform that assays 184 variants across 34 genes. In Cox regression analysis adjusting for age at transplant, pre-transplant chronic kidney disease, pre-transplant diabetes, and the three most significant principal components (PCAs), we did not identify any markers that met our multiple-testing threshold. As a secondary analysis we also modeled post-transplant eGFR directly with linear mixed models adjusted for age at transplant, cyclosporine use, median BMI, and the three most significant principal components. While no SNPs met our threshold for significance, a SNP previously identified in genetic studies of the dosing of tacrolimus CYP3A5 rs776746, replicated in an adjusted analysis at an uncorrected p-value of 0.02 (coeff(S.E.) = 14.60(6.41)). While larger independent studies will be required to further validate this finding, this study underscores the EMRs usefulness as a resource for longitudinal pharmacogenetic study designs
Screening for proximal deep vein thrombosis after acute ischemic stroke: a prospective study using clinical factors and plasma d-dimers
Seasonal Maintenance of Influenza Vaccine-Induced Antibody Response in Kidney Transplant Recipients
Polygenic risk score as a determinant of risk of non-melanoma skin cancer in a European-descent renal transplant cohort
Renal transplant recipients have an increased risk of non-melanoma skin cancer (NMSC) compared to in the general population. Here, we show polygenic risk scores (PRS) calculated from genome-wide association studies (GWAS) of NMSC in general, non-transplant setting, can predict risk of, and time to post-transplant skin cancer. Genetic variants, reaching pre-defined p-value thresholds were chosen from published squamous cell carcinoma (SCC) and basal cell carcinoma (BCC) non-transplant GWAS. Using these genome-wide association studies, BCC and SCC PRS were calculated for each sample across three European-ancestry renal-transplant cohorts (n=889) and tested as predictors of case:control status and time to NMSC post-transplant. BCC PRS calculated at p-value threshold 1x10 was the most significant predictor of case:control status of NMSC post-transplant (OR=1.65; adjusted P=0.0008; AUC(full model adjusted for clinical predictors and PRS)=0.81). SCC PRS at p-value threshold 1x10 was the most significant predictor of time to post-transplant NMSC (adjusted P=8.15x10 ; HR=1.42, concordance (full model)=0.74). PRS of non-transplant NMSC is predictive of case:control status and time to NMSC post-transplant. These results are relevant to how genomics can risk stratify patients to help develop personalised treatment regimens. This article is protected by copyright. All rights reserved