There are no minimally invasive diagnostic metrics for acute kidney transplant rejection (AR), especially in the setting of the common confounding diagnosis, acute dysfunction with no rejection (ADNR). Thus, though kidney transplant biopsies remain the gold standard, they are invasive, have substantial risks, sampling error issues and significant costs and are not suitable for serial monitoring. Global gene expression profiles of 148 peripheral blood samples from transplant patients with excellent function and normal histology (TX; n = 46), AR (n = 63) and ADNR (n = 39), from two independent cohorts were analyzed with DNA microarrays. We applied a new normalization tool, frozen robust multi-array analysis, particularly suitable for clinical diagnostics, multiple prediction tools to discover, refine and validate robust molecular classifiers and we tested a novel one-by-one analysis strategy to model the real clinical application of this test. Multiple three-way classifier tools identified 200 highest value probesets with sensitivity, specificity, positive predictive value, negative predictive value and area under the curve for the validation cohort ranging from 82% to 100%, 76% to 95%, 76% to 95%, 79% to 100%, 84% to 100% and 0.817 to 0.968, respectively. We conclude that peripheral blood gene expression profiling can be used as a minimally invasive tool to accurately reveal TX, AR and ADNR in the setting of acute kidney transplant dysfunction.
BackgroundDespite significant improvements in life expectancy of kidney transplant patients due to advances in surgery and immunosuppression, Chronic Allograft Nephropathy (CAN) remains a daunting problem. A complex network of cellular mechanisms in both graft and peripheral immune compartments complicates the non-invasive diagnosis of CAN, which still requires biopsy histology. This is compounded by non-immunological factors contributing to graft injury. There is a pressing need to identify and validate minimally invasive biomarkers for CAN to serve as early predictors of graft loss and as metrics for managing long-term immunosuppression.MethodsWe used DNA microarrays, tandem mass spectroscopy proteomics and bioinformatics to identify genomic and proteomic markers of mild and moderate/severe CAN in peripheral blood of two distinct cohorts (n = 77 total) of kidney transplant patients with biopsy-documented histology.FindingsGene expression profiles reveal over 2400 genes for mild CAN, and over 700 for moderate/severe CAN. A consensus analysis reveals 393 (mild) and 63 (moderate/severe) final candidates as CAN markers with predictive accuracy of 80% (mild) and 92% (moderate/severe). Proteomic profiles show over 500 candidates each, for both stages of CAN including 302 proteins unique to mild and 509 unique to moderate/severe CAN.ConclusionsThis study identifies several unique signatures of transcript and protein biomarkers with high predictive accuracies for mild and moderate/severe CAN, the most common cause of late allograft failure. These biomarkers are the necessary first step to a proteogenomic classification of CAN based on peripheral blood profiling and will be the targets of a prospective clinical validation study.
BackgroundWhole genome gene expression profiling has revolutionized research in the past decade especially with the advent of microarrays. Recently, there have been significant improvements in whole blood RNA isolation techniques which, through stabilization of RNA at the time of sample collection, avoid bias and artifacts introduced during sample handling. Despite these improvements, current human whole blood RNA stabilization/isolation kits are limited by the requirement of a venous blood sample of at least 2.5 mL. While fingerstick blood collection has been used for many different assays, there has yet to be a kit developed to isolate high quality RNA for use in gene expression studies from such small human samples. The clinical and field testing advantages of obtaining reliable and reproducible gene expression data from a fingerstick are many; it is less invasive, time saving, more mobile, and eliminates the need of a trained phlebotomist. Furthermore, this method could also be employed in small animal studies, i.e. mice, where larger sample collections often require sacrificing the animal. In this study, we offer a rapid and simple method to extract sufficient amounts of high quality total RNA from approximately 70 μl of whole blood collected via a fingerstick using a modified protocol of the commercially available Qiagen PAXgene RNA Blood Kit.ResultsFrom two sets of fingerstick collections, about 70 uL whole blood collected via finger lancet and capillary tube, we recovered an average of 252.6 ng total RNA with an average RIN of 9.3. The post-amplification yields for 50 ng of total RNA averaged at 7.0 ug cDNA. The cDNA hybridized to Affymetrix HG-U133 Plus 2.0 GeneChips had an average % Present call of 52.5%. Both fingerstick collections were highly correlated with r2 values ranging from 0.94 to 0.97. Similarly both fingerstick collections were highly correlated to the venous collection with r2 values ranging from 0.88 to 0.96 for fingerstick collection 1 and 0.94 to 0.96 for fingerstick collection 2.ConclusionsOur comparisons of RNA quality and gene expression data of the fingerstick method with traditionally processed sample workflows demonstrate excellent RNA quality from the capillary collection as well as very high correlations of gene expression data.
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