Spread of α-synuclein pathology through the brain connectome is modulated by selective vulnerability and predicted by network analysis

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Abstract

Studies of patients afflicted by neurodegenerative diseases suggest that misfolded proteins spread through the brain along anatomically connected networks, prompting progressive decline. Recently, mouse models have recapitulated the cell-to-cell transmission of pathogenic proteins and neuron death observed in patients. However, the factors regulating the spread of pathogenic proteins remain a matter of debate due to an incomplete understanding of how vulnerability functions in the context of spread. Here we use quantitative pathology mapping in the mouse brain, combined with network modeling to understand the spatiotemporal pattern of spread. Patterns of α-synuclein pathology are well described by a network model that is based on two factors: anatomical connectivity and endogenous α-synuclein expression. The map and model allow the assessment of selective vulnerability to α-synuclein pathology development and neuron death. Finally, we use quantitative pathology to understand how the G2019S LRRK2 genetic risk factor affects the spread and toxicity of α-synuclein pathology.

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Fig. 1: Quantitation of α-synuclein pathology allows for brain-wide analysis of pathology spread.
Fig. 2: The spread of α-synuclein occurs in a dynamic spatiotemporal pattern throughout the mouse brain.
Fig. 3: Select quantification of cell body pathology allows for assessment of neuron loss.
Fig. 4: Network diffusion model based on anatomical connectivity explains pathological α-synuclein spread.
Fig. 5: In silico seeding of alternative regions in the mouse brain.
Fig. 6: Quantitative α-synuclein pathology mapping allows a direct comparison between NTG and G2019S LRRK2 mice.
Fig. 7: Enhanced spread and toxicity of α-synuclein pathology in resilient regions in G2019S LRRK2 mice.

Data availability

All primary pathology data are available in Supplementary Table 1 and on GitHub (https://github.com/ejcorn/connectome_diffusion). Any other data used to generate the figures in this study are available from the corresponding author upon reasonable request.

Code availability

All code is available at https://github.com/ejcorn/connectome_diffusion. See also the Supplementary Software.

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Acknowledgements

The authors thank members of the laboratory for their feedback in developing this manuscript. This study was supported by the Michael J. Fox Foundation (9530.01 to M.X.H and V.M.Y.L.) and the following NIH grants: T32-AG000255 (to M.X.H. and V.M.Y.L.), P30-AG010124 (to J.Q.T.) and P50-NS053488 (to V.M.Y.L.). D.S.B. also acknowledges support from the John D. and Catherine T. MacArthur Foundation, the ISI Foundation, the Alfred P. Sloan Foundation, the Paul G. Allen Foundation, the National Institute of Neurological Disorders and Stroke (R01 NS099348), and the National Science Foundation (BCS-1441502, BCS-1430087, NSF PHY-1554488 and BCS-1631550).

Author information

M.X.H. conceived and designed the experiments, performed experiments, analyzed results and wrote the manuscript. E.J.C. conceived and designed the experiments, analyzed results, performed network modeling and wrote the manuscript. A.D., B.Z., H.B., R.J.G. and R.M.S. performed experiments. D.S.B., J.Q.T. and V.M.Y.L. conceived and designed the experiments and wrote the manuscript. All authors reviewed and approved the manuscript.

Correspondence to Michael X. Henderson.

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Peer review information: Nature Neuroscience thanks Ellen Kuhl, Tiago Outeiro, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Figs. 1–17.

Reporting Summary

Supplementary Table 1

α-Synuclein pathology values.

Supplementary Software

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