META-ANALYSIS OF SUBSTANTIA NIGRA TRANSCRIPTOME DATA: SEARCHING FOR NEW BIOMARKERS OF PD

The understanding of the genetic basis of the PD and the correlation between genotype and phenotype has revolutionized knowledge about the pathogenetic mechanisms of neurodegeneration, opening up exciting new therapeutic and neuroprotective perspectives. Genomic knowledge for PD is still very open and can provide a good start for studies of the molecular mechanisms that underlie the gene expression variations and the epigenetic mechanisms that may contribute to the complex and characteristic phenotype of PD. Here we use the software TRAM (Transcriptome Mapper), to analyse publicly available microarray data of PD patients and controls substantia nigra, to identify chromosomal segments (Map mode) and gene clusters (Cluster mode) which are biologically relevant in the two different conditions. TRAM integrates original methods for parsing, normalizing, mapping and statistically analyzing expression data; in addition, it is able to easily generate maps showing differential expression between two sample groups, relative to two different biological conditions. We performed a systematic meta-analysis of 143 samples from pool A (patients with PD) and 119 samples from pool B (healthy controls), for a total of respectively 4,128,764 data points (gene expression value) and 3,417,633 data points, relative to 37,580 distinct loci for wich A/B ratio value was determinable. Results obtained included 5 significantly over-expressed segments and 90 over/under-expressed clusters. A list of statistically significant over/under-expressed genes has been generated, including coding genes, ncRNAs and uncharacterized transcripts. This study offers a new approach for the regional analysis of gene expression in neurodegenerative diseases.