bioRxivNeurosciencePreprint
Network analysis of α-synuclein pathology progression reveals p21-activated kinases as regulators of vulnerability
Naman VatsaiD, Julia K. BrynildseniD, Thomas M. GoralskiiD, Kevin KurgatiD, Lindsay K. MeyerdirkiD, Elizabeth BretoniD, Daniella DeWeerdiD, Laura BrasseuriD, Lisa TurneriD, Katelyn BeckeriD, Kristin L. GallikiD, Christine IsaguirreiD, Ryan D. SheldoniD, Danielle S. BassettiD, Michael X. HendersoniD
Abstract
-Synuclein misfolding and progressive accumulation drive a pathogenic process in Parkinson's disease, yet many brain regions develop more or less pathology than would be predicted by connectivity alone, indicating that intrinsic biological factors influence regional vulnerability. Here, we combined whole brain mapping of -synuclein pathology in wildtype mice 3 days to 9 months after seeding with network diffusion modeling based on anatomical connectivity to derive quantitative measures of regional vulnerability. To identify molecular drivers of this vulnerability, we generated a brain-wide sPAtial Neuron Gene Expression Atlas (PANGEA) and compared regional transcriptional profiles with model-derived vulnerability scores. Vulnerable regions were enriched for specific cellular programs. Specific kinases were also enriched in vulnerable regions, leading to the identification of group II p21-activated kinases (PAKs) as candidate regulators of -synucleinopathy. Pharmacological inhibition of group II PAKs reduced -synuclein aggregation and protected against neuron loss in primary neurons, remained effective when administered after pathology initiation, and suppressed pathology in vivo. Consistent with these findings, genetic depletion of PAK5/6 also suppressed -synuclein aggregation. Together, these results establish a framework linking network-level measures to cellular mechanisms of selective vulnerability and nominate group II PAKs as promising disease-modifying therapeutic targets for Parkinson's disease.
- organism: mouse
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: drug response / drug discovery
- approach: statistical model
- approach: experimental assay
- Citations
- 5
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