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| Status |
Public on Jul 20, 2016 |
| Title |
Transcriptome signature in early biopsies of stably functioning kidney allografts identify patients at risk for chronic injury |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by array
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| Summary |
Chronic injury in kidney transplants remains a major cause of graft loss. The aim of this study was to identify a predictive gene set capable of classifying renal grafts at risk for progressive injury due to fibrosis.The Genomics of Chronic Allograft Rejection (GoCAR) study is a prospective, multicenter study. Biopsies obtained prospectively 3 months after transplantation from renal allograft recipients (n=159) with stable renal function were analyzed for gene expression by microarray. Genes were sought which correlated with subsequent 12-month Chronic Allograft Damage Index (CADI) but neither CADI in the 3 month biopsy nor other histological or clinical parameters.
We identifi ed a set of 13 genes that was independently predictive for the development of fi brosis at 1 year (ie, CADI-12 >=2). The gene set had high predictive capacity (area under the curve [AUC] 0·967), which was superior to that of baseline clinical variables (AUC 0·706) and clinical and pathological variables (AUC 0·806). Furthermore routine pathological variables were unable to identify which histologically normal allografts would progress to fi brosis (AUC 0·754), whereas the predictive gene set accurately discriminated between transplants at high and low risk of progression (AUC 0·916). The 13 genes also accurately predicted early allograft loss (AUC 0·842 at 2 years and 0·844 at 3 years). We validated the predictive value of this gene set in an independent cohort from the GoCAR study (n=45, AUC 0·866) and two independent, publically available expression datasets (n=282, AUC 0·831 and n=24, AUC 0·972).
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| Overall design |
Biopsies obtained prospectively 3 months after transplantation from renal allograft recipients (n=159) with stable renal function were analyzed for gene expression by Affymetrix exon arrays. Genes that were specifically correlated with 12-month Chronic Allograft Damage Index (CADI) but neither CADI in the 3 month biopsy nor other histological or clinical parameters were identified by correlation analysis. The minimal geneset was further identified to predict the progressors/non progressors and validated by qPCR in an independent cohort and two public datasets.
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| Contributor(s) |
O’Connell PJ, Zhang W, Menon MC, Yi Z, Schroppel B, Gallon L, Luan Y, Rosales I, Ge Y, Losic B, Xi C, Woytovich C, Keung KL, Wei C, Greene I, Overbey J, Bagiella E, Najafi an N, Samaniego M, Djamali A, Alexander S, Nankivell BJ, Chapman JR, Smith RN, Colvin R, Murphy B |
| Citation(s) |
27452608, 25437874 |
| NIH grant(s) |
| Grant ID |
Grant title |
Affiliation |
Name |
| U01 AI070107 |
Genomics of Chronic Renal Allograft Rejection |
MOUNT SINAI SCHOOL OF MEDICINE |
MURPHY |
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| Submission date |
May 07, 2014 |
| Last update date |
Oct 17, 2019 |
| Contact name |
Weijia Zhang |
| E-mail(s) |
weijia.zhang@mssm.edu
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| Phone |
212-241-2883
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| Organization name |
Mount Sinai School of Medicine
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| Department |
Department of Medicine
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| Lab |
Bioinformatics Lab
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| Street address |
1425 Madison Avenue
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| City |
New York |
| State/province |
NY |
| ZIP/Postal code |
10029 |
| Country |
USA |
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| Platforms (1) |
| GPL5175 |
[HuEx-1_0-st] Affymetrix Human Exon 1.0 ST Array [transcript (gene) version] |
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| Samples (159)
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| Relations |
| BioProject |
PRJNA246389 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE57387_RAW.tar |
3.3 Gb |
(http)(custom) |
TAR (of CEL) |
| Processed data included within Sample table |
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