The Cellular and Extra-Cellular Proteomic Signature of Human Dopaminergic Neurons Carrying the LRRK2 G2019S Mutation
Knab, F.; Guaitoli, G.; Jarboui, M. A.; von Zweydorf, F.; Isik, F. B.; Klose, F.; Rajkumar, A. P.; Gasser, T.; Gloeckner, C. J.
Show abstract
Extracellular vesicles are easily accessible in various biofluids and allow the assessment of disease-related changes of the proteome. This has made them a promising target for biomarker studies, especially in the field of neurodegeneration where access to diseased tissue is very limited. Genetic variants in the LRRK2 gene have been linked to both familial and sporadic forms of Parkinsons disease. With LRRK2 inhibitors entering clinical trials, there is an unmet need for biomarkers that reflect LRRK2-specific pathology and target engagement. In this study, we used induced pluripotent stem cells derived from a patient with Parkinsons disease carrying the LRRK2 G2019S mutation and an isogenic gene corrected control to generate human dopaminergic neurons. We isolated extracellular vesicles and neuronal cell lysates and characterized their proteomic signature using data-independent acquisition proteomics. We performed differential expression analysis and identified 595 significantly differentially regulated proteins in extracellular vesicles and 3205 in cell lysates. Next, we performed gene ontology enrichment analyses on the dysregulated proteins and found close association to biological processes relevant in neurodegeneration and Parkinsons disease. Finally, we focused on proteins that were dysregulated in both the extracellular and cellular proteomes and provide a list of ten promising biomarker candidates that are functionally relevant in neurodegeneration and linked to LRRK2 associated pathology. Among those was the sonic hedgehog signaling molecule, a protein that has tightly been linked to LRRK2-related disruption of cilia function. In conclusion, we characterized the cellular and extracellular proteome of dopaminergic neurons carrying the LRRK2 G2019S mutation and propose an experimentally based list of promising biomarker candidates for future studies.
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