The etiology of
Parkinson's disease is largely unknown. Genome-wide transcriptomic studies in bulk brain tissue have identified several molecular signatures associated with the disease. While these studies have the potential to shed light into the pathogenesis of
Parkinson's disease, they are also limited by two major confounders:
RNA post-mortem degradation and heterogeneous cell type composition of bulk tissue samples. We performed
RNA sequencing following
ribosomal RNA depletion in the prefrontal cortex of 49 individuals from two independent case-control cohorts. Using cell type specific markers, we estimated the cell type composition for each sample and included this in our analysis models to compensate for the variation in cell type proportions.
Ribosomal RNA depletion followed by capture by random primers resulted in substantially more even transcript coverage, compared to
poly(A) capture, in post-mortem tissue. Moreover, we show that cell type composition is a major confounder of differential gene expression analysis in the
Parkinson's disease brain. Accounting for cell type proportions attenuated numerous transcriptomic signatures that have been previously associated with
Parkinson's disease, including vesicle trafficking, synaptic transmission, immune and mitochondrial function. Conversely, pathways related to endoplasmic reticulum,
lipid oxidation and unfolded protein response were strengthened and surface as the top differential gene expression signatures in the
Parkinson's disease prefrontal cortex. Our results indicate that differential gene expression signatures in
Parkinson's disease bulk brain tissue are significantly confounded by underlying differences in cell type composition. Modeling cell type heterogeneity is crucial in order to unveil transcriptomic signatures that represent regulatory changes in the
Parkinson's disease brain and are, therefore, more likely to be associated with underlying disease mechanisms.