PD is a common and etiologically complex disease, whose pathological hallmarks are the
deposition of LB and the selective degeneration of MDAs in the SNpc.
So far, the mechanisms underlying this selective degeneration are poorly understood. aSyn
misfolding and aggregation, impairment of synaptic function, energy metabolism and
protein degradation as well as activation of the immune system have all been implicated in
the pathogenesis of PD. However, how this processes preferentially affect MDAs is
unknown, as are the exact mechanisms linking normal MDA function, LBP and
neurodegeneration. GWAS studies have provided important insight into the genetics and
pathophysiology of sporadic PD. However, the majority of common disease variants lie
within the non-protein coding sequence and confer only a modest increase in risk.
Therefore, the exact processes by which this variants increase the risk for PD are unknown.
Here we have, for the first time, combined LCD and RNASeq, to create a comprehensive
catalog of all transcribed coding and non-coding elements specifically in MDAs from snap
frozen human brains in HC, ILBD and PD. We found that 33 % of all known GENECODE
annotated transcripts in MDAs are ncRNAs and that this transcripts are expressed at high
levels of transcription. In total we identified 329 processed RNAs, 2,255 lincRNAs, 2,175
natural antisense RNAs and 2,672 expressed pseudogenes, many of which had never been
described before in the human brain. In addition we identified 71,022 unknown transcribed
ncRNAs that were expressed at low to moderate levels of transcription. Interestingly, we
found that ncRNAs, unlike mRNAs, can be strongly and selectively turned on in some
individuals, while being switched off in others. This could point towards an important role of
this class of transcripts in adjusting the function of the genome towards the specific needs
of an individual (eg. ageing, environmental factors, common genetic variants). We identified
a set of 698 mRNAs and 1,525 ncRNAs that were expressed only in MDAs but not PCs and
therefore considered the MDA-specific part of the transcriptome. Using t-SNE, hierarchical
clustering and coexpression analysis we could demonstrate that these transcripts are highly
specific and representative for MDAs and likely to be tightly coregulated. In addition, using
DeSeq, we identified 645 mRNAs and 202 ncRNAs that where significantly differentially
expressed between MDAs and PCs. While the majority of differentially expressed
transcripts were mRNAs, many specific transcripts were ncRNAs or TFs. ORA among
MDA-specific mRNAs showed enrichment for molecular signaling, biologic oxidations and
the immune response pathways. This suggests major differences in the way MDAs and
PCs handle neurotransmitters, xenobiotic substances or inflammatory stimuli. In addition,
energy usage regulated by INS-signaling was identified as another major MDA-specific
pathway.
In the next step we correlated the entire transcriptome in MDAs from HC, ILBD and PD
brains with their respective Lewy Body stages, followed by GSEA to identify the molecular
pathways and potential master regulators that are driving the pathological process. Of the
18,875 mRNAs and 19,034 ncRNAs used for correlation, only 1,509 mRNAs and 885
ncRNAs reached significance at a nominal P value of <= 0.05 and 64 mRNAs and 3
ncRNAs at a FDR < 25 %. This generally rather weak association of individual gene
expression with LBD (spearman rho 0.20 to 0.42, P value 1.5e-05 to 4.5e-02) is in line with the
findings from GWAS studies, indicating that common genetic variants confer only a modest
increase in risk for sporadic PD. By using GSEA and the C3 component of TF binding
motives in the Broad Institutes MSigDB we identified three TF binding sites (FOXO4, NFAT,
TAX/CREB) that were strongly enriched (FDR 0,7-10 %) in genes positively correlated with
LBP and one TF binding site (CP2) that was enriched in genes that were negatively
correlated (FDR 13 %). Interestingly, extensive in-vitro and in-vivo evidence exists, linking
the FOXO class of transcription factors and NFAT to the pathogenesis of PD. In addition
TAX/CREB has been implicated in neurodegenerative diseases and the regulation of
PGC1α, another gene linked to the pathogenesis of PD. We therefore suggest that these
TFs could function as master regulators that either cause or sustain the degeneration of
MDAs in PD. Using the C2 component of the MSigDB we identified an upregulation of antiinflammatory,
amine and GPCR singaling as well as a downregulation in genes involved in
energy utilization, glycosphingolipid metabolism, as well as the dopaminergic differentiation
and vesicle trafficking. This supports our findings from previous studies, indicating an
orchestrated downregulation of genes involved in insulin signaling and the ETC with
progressing LBD. In addition, dysfunction of glycosphingolipid metabolism has been linked
at many levels with the pathophysiology of PD. Finally, the downregulation of the genes
involved in dopamine metabolism and signaling indicates an important loss of normal
function in MDAs with increasing LB burden. On the other hand, the activation of antiinflammatory
IL-10 signaling might suggest a more active role of this cells in
neuroinflammation then has been previously assumed.
Taken together, we identified a huge and understudied population of non-coding transcripts
in MDAs. In addition, we could demonstrate a unique pattern of cell type specific expression
for genes involved in cellular signaling, energy metabolism and the immune system in
MDAs as well as a coordinated shift in the expression of the same pathways with increasing
LBP. It therefore appears likely that the same pathways that are responsible for the
differential vulnerability of this cell type are also causing or sustaining the pathological
process in PD. In addition we identified a defined set of TFs that might drive this processes.
Consequently, we suggest that future disease modifying or curative treatment approaches
should focus on modulating one or a combination of these pathways, possibly by targeting
the respective master regulator TFs.
David Gritsch