Analysis of the Major Histocompatibility Complex in Graft Rejection Revisited by Gene Expression Profiles

Influence of cytokine and intercellular adhesion molecule-1 gene polymorphisms on acute rejection in pediatric renal transplantation

Immune response regulation by cytokines is a key to understanding AGR. The influence of the functional polymorphisms in genes coding for TNF-alpha (-308G > A), IL-10 (-819C > T, and -1082A > G), IFN-gamma [(CA)n], TGF-beta1 (+869T > C), and iCAM-1 (R241G and E469K), in addition to HLA and gender matching on the presentation of AGR in 51 pediatric renal recipients during a 36-month post-transplantation follow-up were analyzed. Also, donors and a control group were genotyped. All groups were within Hardy-Weinberg equilibrium for all polymorphisms except IL-10-819C > T and TNF-alpha (p < 0.005 and p < 0.01, respectively) in recipients. Transplants with gender mismatch showed a higher risk for AGR than those between individuals with gender match (OR, 4.227; p = 0.010). Recipients with a high-production compared with low-production TNF-alpha allele experienced earlier AGR (p = 0.030), and those with high-production alleles of both TNF-alpha and IFN-gamma showed a further increased risk (OR = 11.129, p = 0.024). These findings support the notion that a single genotype cannot by itself explain an event as complex as AGR. The sum or combination of different specific alleles of these genes could better account for the immune response to an allograft.

Novel insights into lung transplant rejection by microarray analysis

Gene expression microarrays can estimate the prevalence of mRNA for thousands of genes in a small sample of cells or tissue. Organ transplant researchers are increasingly using microarrays to identify specific patterns of gene expression that predict and characterize acute and chronic rejection, and to improve our understanding of the mechanisms underlying organ allograft dysfunction. We used microarrays to assess gene expression in bronchoalveolar lavage cell samples from lung transplant recipients with and without acute rejection on simultaneous lung biopsies. These studies showed increased expression during acute rejection of genes involved in inflammation, apoptosis, and T-cell activation and proliferation. We also studied gene expression during the evolution of airway obliteration in a murine heterotopic tracheal transplant model of chronic rejection. These studies demonstrated specific patterns of gene expression at defined time points after transplantation in allografts, whereas gene expression in isografts reverted back to that of native tracheas within 2 wk after transplantation. These studies demonstrate the potential power of microarrays to identify biomarkers of acute and chronic lung rejection. The application of new genetic, genomic, and proteomic technologies is in its infancy, and the microarray-based studies described here are clearly only the beginning of their application to lung transplantation. The massive amount of data generated per tissue or cell sample has spawned an outpouring of invention in the bioinformatics field, which is developing methodologies to turn data into meaningful and reproducible clinical and mechanistic inferences.