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

TL;DR

This study shows how the LRRK2 G2019S mutation affects human neural networks, causing abnormal structure and function at different scales.

Contribution

The study reveals novel micro-and mesoscale neurodegenerative dynamics in human neural networks with the LRRK2 G2019S mutation.

Findings

Neurons with the LRRK2 G2019S mutation formed networks with abnormal morphology and mitochondrial dynamics.

These networks showed heightened metabolic demand and reduced resilience to perturbation.

Structure–function relationships were altered at both micro-and mesoscales in mutated networks.

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.

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