Gene expression profiles of circulating leukocytes correlate with @entity8 activity in IgA XXXX .

@entity1 @entity644 @entity8 @entity66 @entity628 @entity1988 @entity6994 @entity1011 @entity811 @entity631
BACKGROUND: The goal of these studies was to explore the possibility of using gene expression profiles of circulating leukocytes as a functional fingerprint of @entity66 activity. METHODS: This feasibility study utilized IgA @entity8 ( @entity6994 ) as a model system. Genes differentially expressed in @entity6994 @entity1 were identified by Affymetrix GeneChip microarrays, and compared with gene expression of @entity628 ( @entity628 ), minimal change disease, antineutrophil cytoplasmic antibody (ANCA) @entity631 , and with healthy volunteers. Of the genes identified, 15 transcriptionally up-regulated were validated in a larger cohort of @entity1 using TaqMan polymerase chain reaction (PCR). To test whether increased expression of these genes correlated with disease activity, cluster analyses were performed utilizing the TaqMan PCR values. Taking a mathematical approach, we tested whether gene expression values were correlative with kidney function, as reflected by serum @entity1011 and @entity1011 clearance values. RESULTS: We identified 15 genes significantly correlative with disease activity in @entity6994 . This gene signature of @entity6994 @entity1 ' leukocytes reflected kidney function. This was demonstrated in that mathematically generated theoretical values of serum @entity1011 and @entity1011 clearance correlated significantly with actual @entity6994 @entity1 values of serum @entity1011 and @entity1011 clearance. There was no apparent correlation with @entity811 and @entity644 . The expression levels of this same gene set in ANCA @entity631 or @entity1988 @entity1 were not correlative with serum @entity1011 or @entity1011 clearance values. CONCLUSION: These data indicate that leukocytes carry informative disease-specific markers of pathogenic changes in renal tissue.
