Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Recipient myeloid cell subsets in transplanted allografts

ABSTRACT: Balb/c donor hearts were transplanted into C57/BL6 recipients as previously described (Corry et al, 1973). Recipient mice were treated with 250μg anti-CD40L mAb for tolerance induction on days 0, 2, and 4 as previously described (Jiang et al., 2011) or left untreated. On day 5 after transplantation graft infiltrating myeloid subsets were isolated using fluorescence activated cell sorting (FACS). Affymetrix Mouse Gene arrays were run in triplicate with the samples of interest. Raw CEL file data from Affymetrix Expression Console were background corrected, normalized, and summarized using RMA. 18 Samples, 9 treated and 9 untreated, 3 replicates each

ORGANISM(S): Mus musculus

SUBMITTER: Jordi Ochando

PROVIDER: E-GEOD-68648 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description: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 identified 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). 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. This dataset is part of the TransQST collection.

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Recipient myeloid cell subsets in transplanted allografts

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