Video_1_Micro-and mesoscale aspects of neurodegeneration in engineered human neural networks carrying the LRRK2 G2019S mutation.AVI

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.</p

Video_2_Micro-and mesoscale aspects of neurodegeneration in engineered human neural networks carrying the LRRK2 G2019S mutation.AVI

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.</p

Table_1_Micro-and mesoscale aspects of neurodegeneration in engineered human neural networks carrying the LRRK2 G2019S mutation.docx

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.</p

Data_Sheet_1_Micro-and mesoscale aspects of neurodegeneration in engineered human neural networks carrying the LRRK2 G2019S mutation.PDF

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.</p

Litter differences in DTI metrics.

<p>Fractional anisotropy (a); mean (b), radial (c) and axial diffusivity (d) in white matter areas of litter A (grey columns, n = 13), B (black columns, n = 9) and controls (white columns, n = 8) on postnatal day 14. Mean, axial and radial diffusivity are shown in units of mm²/s. Data are presented as mean ± 95% confidence interval. Differences between litters are marked where significant (<i>p</i> < 0.05). Abbreviations: wm: all of white matter; bcc: corpus callosum (body); ec: external capsule; ic: internal capsule; IHH, intermittent hyperoxia-hypoxia; hf: hippocampal fimbriae. </p

Retina.

<p>(a-d): H&E retinal slices from control (a) and IHH animals at P14 (b-d) showing haemorrhage in the ganglion cell layer (b), inner nuclear layer (c) and outer nuclear cell layer (d). (e-h): Retinal wholemounts stained with endothelial-specific Biotinylated <i>Griffonia</i> (<i>Bandeiraea</i>) <i>Simplicifolia</i> Lectin I Isolectin B4 from controls at P28 with a mature vascular bed (e) and no vasculature extending beyond the ora serrata (f). Retinal vascular bed in IHH animal at P28 with less remodelling (g) and areas of vascularization beyond the ora serrata (h). (a-d): x400 magnification; scale bar = 50 μm. (e-h): x100 magnification; scale bar = 200 μm. Abbreviations, IHH, intermittent hyperoxia-hypoxia; P14, postnatal day 14; P28, postnatal day 28.</p

Vascular density.

<p>(a) Vascular density as % of controls (white columns, n = 4) in IHH animals at P14 (grey columns; IHH: n = 10) and P28 (black columns; IHH: n = 12). Data are expressed as mean ± 95% confidence intervals. (b-e) x400 magnification of lectin-stained endothelium in IHH (upper row) and control (lower row) at P14 (b & d) and P28 (c & e). *<i>p</i> = 0.005 IHH vs. control. Scale bar = 50 μm. Abbreviations: IHH, intermittent hyperoxia-hypoxia; P14, postnatal day 14; P28, postnatal day 28; pvwm, periventricular white matter. </p

DTI on postnatal day 14.

<p>Fractional anisotropy (a); radial (b); mean (c) and axial diffusivity (d) in white matter areas of controls (grey columns, n = 8) and IHH (black columns, n = 22). Mean, axial and radial diffusivity are shown in units of mm²/s. Data are presented as mean ± 95% confidence interval.* <i>p</i> < 0.04. Abbreviations: wm: all of white matter; bcc: corpus callosum (body); ec: external capsule; ic: internal capsule; IHH, intermittent hyperoxia-hypoxia; hf: hippocampal fimbriae. </p

Rotarod testing.

<p>Mean time on a Rotarod on P20 and P27 of IHH (n = 12, black diamonds) and controls (n = 4, grey boxes). *<i>p</i> ≤ 0.03 IHH vs. control. Data are presented as mean ± 95% confidence intervals. Abbreviations: IHH, intermittent hyperoxia-hypoxia; P20, postnatal day 20; P27, postnatal day 27.</p

Litter differences in T₂.

<p>T₂-relaxation time in the brain at P14 in litter A (grey columns, n = 13), litter B (black columns, n = 9) and C (white columns, n = 8) in the cortex (a), hippocampus (b), putamen (c) and thalamus (d). T₂-relaxation times are shown in milliseconds. Differences between litters are marked where significant (<i>p</i> < 0.05). Data are presented as mean ± 95% confidence interval. Abbreviations: IHH, intermittent hyperoxia-hypoxia; P14: postnatal day 14; P28: postnatal day 28. </p