Dataset Information

Identification of biomarkers to assess organ quality and predict posttransplantation outcomes.

ABSTRACT: The increased disparity between organ supply and need has led to the use of extended criteria donors and donation after cardiac death donors with other comorbidities.We have examined the preimplantation transcriptome of 112 kidney transplant recipient samples from 100 deceased-donor kidneys by microarray profiling. Subject groups were segregated based on estimated glomerular filtration rate (eGFR) at 1 month after transplantation: the GFR-high group (n=74) included patients with eGFR 45 mL/min per 1.73 m(2), whereas the GFR-low group (n=35) included patients with eGFR 45 mL/min or less per 1.73 m(2).Gene expression profiling identified higher expression of 160 probe sets (140 genes) in the GFR-low group, whereas expression of 37 probe sets (33 genes) was higher in the GFR-high group (P<0.01, false discovery rate <0.2). Four genes (CCL5, CXCR4, ITGB2, and EGF) were selected based on fold change and P value and further validated using an independent set of samples. A random forest analysis identified three of these genes (CCL5, CXCR4, and ITGB2) as important predictors of graft function after transplantation.Inclusion of pretransplantation molecular gene expression profiles in donor quality assessment systems may provide the necessary information for better donor organ selection and function prediction. These biomarkers would further allow a more objective and complete assessment of procured renal allografts at pretransplantation time.

SUBMITTER: Scian MJ

PROVIDER: S-EPMC3927314 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

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Identification of biomarkers to assess organ quality and predict posttransplantation outcomes.

Scian Mariano J MJ Maluf Daniel G DG Archer Kellie J KJ Turner Stephen D SD Suh Jihee L JL David Krystle G KG King Anne L AL Posner Marc P MP Brayman Kenneth L KL Mas Valeria R VR

Transplantation 20121001 8

<h4>Unlabelled</h4>The increased disparity between organ supply and need has led to the use of extended criteria donors and donation after cardiac death donors with other comorbidities.<h4>Methods</h4>We have examined the preimplantation transcriptome of 112 kidney transplant recipient samples from 100 deceased-donor kidneys by microarray profiling. Subject groups were segregated based on estimated glomerular filtration rate (eGFR) at 1 month after transplantation: the GFR-high group (n=74) incl ...[more]

PMID: 22992769

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Project description:Rationale & objectiveThere is debate on whether weight loss, a hallmark of frailty, signals higher risk for adverse outcomes among recipients of deceased donor kidney transplantation (DDKT).Study designRetrospective cohort study.Setting & participantsUsing national Organ Procurement and Transplantation Network data, we included all DDKT recipients in the United States between December 4, 2004, and December 3, 2014, who were adults (aged ≥ 18 years) when listed for DDKT.ExposuresRelative pre-DDKT weight change as a continuous predictor and categorized as <5% weight change from listing to DDKT, ≥5% to <10% weight loss, ≥10% weight loss, ≥5% to <10% weight gain, and ≥10% weight gain.OutcomesWe examined 3 post-DDKT outcomes: (1) transplant hospitalization length of stay (LOS) in days, (2) all-cause graft failure, and (3) mortality.Analytic approachUnadjusted fractional polynomial methods, multivariable log-gamma models, and multivariable Cox proportional hazards models.ResultsAmong 94,465 recipients of DDKT, median pre-DDKT weight change was 0 (interquartile range, -3.5 to +3.9) kg. There were nonlinear unadjusted associations between relative pre-DDKT weight loss and longer transplant hospitalization LOS, higher all-cause graft loss, and higher mortality. Compared with recipients with <5% pre-DDKT weight change (n = 49,366; 52%), recipients who lost ≥10% of their listing weight (n = 10,614; 11%) had 0.66 (95% CI, 0.23-1.09) days longer average transplant hospitalization LOS (P = 0.003), 1.11-fold higher graft loss (adjusted HR [aHR], 1.11; 95% CI, 1.06-1.17; P < 0.001), and 1.18-fold higher mortality (aHR, 1.18; 95% CI, 1.11-1.25; P < 0.001) independent of recipient, donor, and transplant factors. Pre-DDKT dialysis exposure, listing body mass index category, and waiting time modified the association of pre-DDKT weight change with hospital LOS (interaction P < 0.10), but not with all-cause graft loss and mortality.LimitationsUnmeasured confounders and inability to identify volitional weight change. Also, the higher significance level set to increase the power of detecting interactions with the fixed sample size may have resulted in increased risk for type 1 error.ConclusionsDDKT recipients with ≥10% pre-DDKT weight loss are at increased risk for adverse outcomes and may benefit from augmented support post-DDKT.

Project description:BackgroundLandmark clinical trials have led to optimal treatment recommendations for patients with diabetes. Whether optimal treatment is actually delivered in practice is even more important than the efficacy of the drugs tested in trials. To this end, treatment quality indicators have been developed and tested against intermediate outcomes. No studies have tested whether these treatment quality indicators also predict hard patient outcomes.MethodsA cohort study was conducted using data collected from >10.000 diabetes patients in the Groningen Initiative to Analyze Type 2 Treatment (GIANTT) database and Dutch Hospital Data register. Included quality indicators measured glucose-, lipid-, blood pressure- and albuminuria-lowering treatment status and treatment intensification. Hard patient outcome was the composite of cardiovascular events and all-cause death. Associations were tested using Cox regression adjusting for confounding, reporting hazard ratios (HR) with 95% confidence intervals.ResultsLipid and albuminuria treatment status, but not blood pressure lowering treatment status, were associated with the composite outcome (HR?=?0.77, 0.67-0.88; HR?=?0.75, 0.59-0.94). Glucose lowering treatment status was associated with the composite outcome only in patients with an elevated HbA1c level (HR?=?0.72, 0.56-0.93). Treatment intensification with glucose-lowering but not with lipid-, blood pressure- and albuminuria-lowering drugs was associated with the outcome (HR?=?0.73, 0.60-0.89).ConclusionTreatment quality indicators measuring lipid- and albuminuria-lowering treatment status are valid quality measures, since they predict a lower risk of cardiovascular events and mortality in patients with diabetes. The quality indicators for glucose-lowering treatment should only be used for restricted populations with elevated HbA1c levels. Intriguingly, the tested indicators for blood pressure-lowering treatment did not predict patient outcomes. These results question whether all treatment indicators are valid measures to judge quality of health care and its economics.

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Identification of biomarkers to assess organ quality and predict posttransplantation outcomes.

Publications

Identification of biomarkers to assess organ quality and predict posttransplantation outcomes.

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