ABSTRACT
Large-scale genomics approaches are now widely utilized to study a myriad of human diseases. These powerful techniques, when combined with data analysis tools, detect changes in transcript abundance in diseased tissue relative to control. We hypothesize that specific differential gene expression underlies important pathogenic processes in Parkinson's disease, which is characterized by the gradual loss of dopaminergic neurons in the substantia nigra and consequent loss of dopamine in the striatum. We have therefore examined gene expression levels in the human parkinsonian nigrostriatal pathway, and compared them with those of neurologically normal controls. Using unsupervised clustering methods, we demonstrate that relatively few genes' expression levels can effectively distinguish between disease and control brains. Further, we identify several interesting patterns of gene expression that illuminate pathogenic cascades in Parkinson's disease. In particular is the robust loss of synaptic gene expression in diseased substantia nigra and striatum.
