Studies of gene expression in the Parkinson’s disease brain

Parkinson’s disease (PD) is the second most prevalent neurodegenerative disorder, affecting ~1.8% of the population above 65 years. A combination of genetic and environmental factors contributes to the risk of PD, but the molecular mechanisms underlying its aetiology remain largely unaccounted for. Profiling gene expression in the PD brain can identify molecular processes associated with the pathogenesis and nominate candidate therapeutic targets for further study. Most previous gene expression studies in PD focused on specific hypotheses and were restricted to selected genes of interest and only few were performed transcriptome-wide. While in part informative, the results of these studies must be interpreted with caution due to a combination of technical and biological limitations. Factors applying specifically to the study of human bulk brain tissue make it difficult to confidently and accurately determine altered pathways. 1) Bulk brain tissue is composed of multiple cell types, some of which are selectively affected in PD. Variation in cell-type composition across samples introduces noise, while disease-associated changes in the number of neurons and glia introduce systematic gene expression biases between conditions. 2) The complex architecture of neurons complicates sample dissection and can result in variable soma-to-synapses ratios across samples. This variability results in additional noise in expression data since RNA and proteins can undergo axonal transport, with some preferentially localizing to the soma or synapses. Another limitation of previous studies is that gene-level analyses provide only an incomplete perspective on the expression landscape. Regulation at the transcript- and protein-level is often overlooked. The work of this thesis comprises three alternative approaches of gene expression analyses in the PD brain, aiming to overcome these limitations. We employed RNA-Seq and mass spectrometry in the prefrontal cortex of PD patients and healthy controls and approached these challenges by profiling expression at transcript-, gene- and protein-level. Considering the described aspects of bulk brain tissue, we adjusted for changes in cellular composition, RNA quality and guided functional interpretation with the polarized nature of neurons in mind. Our results indicate that the frequently reported downregulation of mitochondrial function is partly driven by cellular composition. Adjusting for cell-type bias instead revealed altered pathways related to protein degradation, further strengthening their involvement in disease pathology. Both differential gene and transcript isoform expression showed enrichment for these. Additionally, we nominated genes that exhibit differential transcript usage events, suggesting alternate regulation at the transcript-level. These candidates can be targeted in future studies to identify functional consequences. Finally, we observed discordance between transcriptome and proteome which we concluded reflects alterations in PD proteostasis. Specifically, we identified certain proteasomal subunits central to these regulatory changes, providing us with further evidence for the key role of protein degradation in PD brain