Micro-and mesoscale aspects of neurodegeneration in engineered human neural networks carrying the LRRK2 G2019S mutation

Abstract

Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene have been widely linked to Parkinson’s disease, where the G2019S variant has been shown to contribute uniquely to both familial and sporadic forms of the disease. LRRK2-related mutations have been extensively studied, yet the wide variety of cellular and network events related to these mutations remain poorly understood. The advancement and availability of tools for neural engineering now enable modeling of selected pathological aspects of neurodegenerative disease in human neural networks in vitro. Our study revealed distinct pathology associated dynamics in engineered human cortical neural networks carrying the LRRK2 G2019S mutation compared to healthy isogenic control neural networks. The neurons carrying the LRRK2 G2019S mutation self-organized into networks with aberrant morphology and mitochondrial dynamics, affecting emerging structure–function relationships both at the micro-and mesoscale. Taken together, the findings of our study points toward an overall heightened metabolic demand in networks carrying the LRRK2 G2019S mutation, as well as a resilience to change in response to perturbation, compared to healthy isogenic controls.

Engineered Cortical Microcircuits for Investigations of Neuroplasticity

“…Microfluidic models harbor substantial, albeit underutilized, potential for elucidating pathological mechanisms and propagation of relevant dynamics within controlled microenvironments (76, 77). For example, several studies have illustrated how the dysfunction of one node affects the function of connected healthy nodes in various diseases, including how misfolded protein aggregates can spread in such networks (11,(78)(79)(80)(81). A key advantage of the presented model system is that it enables the application of localized perturbations to individual nodes within a complex network hierarchy, while allowing precise monitoring of spatiotemporal changes in neighboring areas, as demonstrated.…”

Evolving alterations of structural organization and functional connectivity in feedforward neural networks after induced P301L tau mutation

“…Such networks develop with progressively increasing structural and functional complexity over time, recapitulating fundamental aspects of neural network behavior as seen in the brain (Collingridge et al, 2010;Valderhaug et al, 2021;van de Wijdeven et al, 2019;Winter-Hjelm N, 2023). Engineered in vitro models thus enable longitudinal studies of dynamic network behavior and allow for selective perturbation and monitoring of network responses at the micro-and mesoscale level (Bauer et al, 2022;Bruno et al, 2020;Fiskum et al, 2021;Gribaudo et al, 2019;Nonaka et al, 2011;Valderhaug et al, 2021;Valderhaug et al, 2024;Weir et al, 2023).…”