An association of candidate gene haplotypes and bleeding severity in von Willebrand disease (VWD) type 1 pedigrees.

von Willebrand disease (VWD) type 1 is difficult to diagnose because of bleeding variability and low heritability of von Willebrand factor (VWF) levels. We compared a bleeding severity score and bleeding times to candidate gene haplotypes within pedigrees of 14 index cases, using a covariance components model for multivariate traits (Mendel: QTL Association). These pedigrees included 13 affected and 40 unaffected relatives, as defined by plasma ristocetin cofactor (VWF:RCo) levels. The bleeding severity score was derived from a detailed history. Donors were genotyped using a primer extension method, and 9 candidate genes were selected for analysis. VWF:RCo levels had the strongest influence on bleeding severity score and bleeding time. ITGA2 haplotype 2 (807C) and ITGA2B haplotype 1 (Ile(843)) were each associated with increased bleeding severity scores (P < .01 and P < .01, respectively). GP6 haplotype b (Pro(219)) was also associated with increased scores (P = .03) after adjustment for donor age. No association was observed with 6 other candidate genes, GP1BA, ITGB3, VWF, FGB, IL6, or TXA2R. Increased plasma VWF:Ag levels were associated with VWF haplotype 1 (-1793G; P = .02). These results establish that genetic differences in the adhesion receptor subunits alpha(2), alpha(IIb,) and GPVI can influence the phenotype of VWD type 1.

Kidney transplant rejection and tissue injury by gene profiling of biopsies and peripheral blood lymphocytes.

A major challenge for kidney transplantation is balancing the need for immunosuppression to prevent rejection, while minimizing drug-induced toxicities. We used DNA microarrays (HG-U95Av2 GeneChips, Affymetrix) to determine gene expression profiles for kidney biopsies and peripheral blood lymphocytes (PBLs) in transplant patients including normal donor kidneys, well-functioning transplants without rejection, kidneys undergoing acute rejection, and transplants with renal dysfunction without rejection. We developed a data analysis schema based on expression signal determination, class comparison and prediction, hierarchical clustering, statistical power analysis and real-time quantitative PCR validation. We identified distinct gene expression signatures for both biopsies and PBLs that correlated significantly with each of the different classes of transplant patients. This is the most complete report to date using commercial arrays to identify unique expression signatures in transplant biopsies distinguishing acute rejection, acute dysfunction without rejection and well-functioning transplants with no rejection history. We demonstrate for the first time the successful application of high density DNA chip analysis of PBL as a diagnostic tool for transplantation. The significance of these results, if validated in a multicenter prospective trial, would be the establishment of a metric based on gene expression signatures for monitoring the immune status and immunosuppression of transplanted patients.