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Spread of α-synuclein pathology through the brain connectome is modulated by selective vulnerability and predicted by network analysis
Open accessAbstract
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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“The arguments for synaptic spread are somewhat weakened by the fact that aggregate spread happens in both antero- and retrograde directions across regions that are anatomical neighbors (68).”
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Generalized Additive Models: An Introduction with R
Wood, S. N. (2017) · doi:10.1201/9781315370279 · Cited by 13,852
Staging of brain pathology related to sporadic Parkinson’s disease
Braak, H., Tredici, K. D., Rüb, U., de Vos, R. A. I., Jansen Steur, E. N. H., & Braak, E. (2003) · Neurobiology of Aging · doi:10.1016/s0197-4580(02)00065-9 · Cited by 10,777
Wood, S. N. (2010) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.1467-9868.2010.00749.x · Cited by 7,538
Genome-wide atlas of gene expression in the adult mouse brain
Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., et al. (2007) · Nature · doi:10.1038/nature05453 · Cited by 5,572
Wood, S. N. (2006) · doi:10.1201/9781420010404 · Cited by 4,953
Spillantini, M. G., Crowther, R. A., Jakes, R., Hasegawa, M., & Goedert, M. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.11.6469 · Cited by 2,868
A mesoscale connectome of the mouse brain
Oh, S. W., Harris, J. A., Ng, L., Winslow, B., Cain, N., Mihalas, S., Wang, Q., Lau, C., Kuan, L., Henry, A. M., et al. (2014) · Nature · doi:10.1038/nature13186 · Cited by 2,612
Luk, K. C., Kehm, V., Carroll, J., Zhang, B., O’Brien, P., Trojanowski, J. Q., & Lee, V. M.-Y. (2012) · Science · doi:10.1126/science.1227157 · Cited by 2,563
Self-citationStable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models
Wood, S. (2004) · Journal of the American Statistical Association · doi:10.1198/016214504000000980 · Cited by 2,046
(1998) · Europe PMC (PubMed Central) · Cited by 1,594
Self-citationVolpicelli-Daley, L. A., Luk, K. C., Patel, T. P., Tanik, S. A., Riddle, D. M., Stieber, A., Meaney, D. F., Trojanowski, J. Q., & Lee, V. M.-Y. (2011) · Neuron · doi:10.1016/j.neuron.2011.08.033 · Cited by 1,569
Self-citationHealy, D. G., Falchi, M., O'Sullivan, S. S., Bonifati, V., Durr, A., Bressman, S., Brice, A., Aasly, J., Zabetian, C. P., Goldwurm, S., et al. (2008) · The Lancet Neurology · doi:10.1016/s1474-4422(08)70117-0 · Cited by 1,425
Parkinson's disease-associated mutations in leucine-rich repeat kinase 2 augment kinase activity
West, A. B., Moore, D. J., Biskup, S., Bugayenko, A., Smith, W. W., Ross, C. A., Dawson, V. L., & Dawson, T. M. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0507360102 · Cited by 1,228
Selective neuronal vulnerability in Parkinson disease
Surmeier, D. J., Obeso, J. A., & Halliday, G. M. (2017) · Nature Reviews Neuroscience · doi:10.1038/nrn.2016.178 · Cited by 1,116
Spillantini, M. G., Crowther, R. A., Jakes, R., Cairns, N. J., Lantos, P. L., & Goedert, M. (1998) · Neuroscience Letters · doi:10.1016/s0304-3940(98)00504-7 · Cited by 1,052
Luk, K. C., Song, C., O'Brien, P., Stieber, A., Branch, J. R., Brunden, K. R., Trojanowski, J. Q., & Lee, V. M.-Y. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0908005106 · Cited by 938
Self-citationVolpicelli-Daley, L. A., Luk, K. C., & Lee, V. M.-Y. (2014) · Nature Protocols · doi:10.1038/nprot.2014.143 · Cited by 731
Self-citationA network diffusion model of disease progression in dementia
Raj, A., Kuceyeski, A., & Weiner, M. (2012) · Neuron · doi:10.1016/j.neuron.2011.12.040 · Cited by 723
Braak, H., Tredici, K. D., Bratzke, H., Hamm-Clement, J., Sandmann-Keil, D., & Rüb, U. (2002) · Journal of Neurology · doi:10.1007/s00415-002-1301-4 · Cited by 710
the Arizona Parkinson’s Disease Consortium, Beach, T. G., Adler, C. H., Lue, L., Sue, L. I., Bachalakuri, J., Henry-Watson, J., Sasse, J., Boyer, S., Shirohi, S., et al. (2009) · Acta Neuropathologica · doi:10.1007/s00401-009-0538-8 · Cited by 698
Pathological α-synuclein transmission initiated by binding lymphocyte-activation gene 3
Mao, X., Ou, M. T., Karuppagounder, S. S., Kam, T.-I., Yin, X., Xiong, Y., Ge, P., Umanah, G. E., Brahmachari, S., Shin, J.-H., et al. (2016) · Science · doi:10.1126/science.aah3374 · Cited by 690
Kinase activity is required for the toxic effects of mutant LRRK2/dardarin
Greggio, E., Jain, S., Kingsbury, A., Bandopadhyay, R., Lewis, P., Kaganovich, A., van der Brug, M. P., Beilina, A., Blackinton, J., Thomas, K. J., et al. (2006) · Neurobiology of Disease · doi:10.1016/j.nbd.2006.04.001 · Cited by 671
LRRK2 activation in idiopathic Parkinson’s disease
Maio, R. D., Hoffman, E. K., Rocha, E. M., Keeney, M. T., Sanders, L. H., Miranda, B. R. D., Zharikov, A., Laar, A. D. V., Stepan, A. F., Lanz, T. A., et al. (2018) · Science Translational Medicine · doi:10.1126/scitranslmed.aar5429 · Cited by 580
Tong, Y., Yamaguchi, H., Giaime, E., Boyle, S., Kopan, R., Kelleher, R. J., & Shen, J. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1004676107 · Cited by 521
The physics of brain network structure, function and control
Lynn, C. W., & Bassett, D. S. (2019) · Nature Reviews Physics · doi:10.1038/s42254-019-0040-8 · Cited by 452
Self-citationRamonet, D., Daher, J. P. L., Lin, B. M., Stafa, K., Kim, J., Banerjee, R., Westerlund, M., Pletnikova, O., Glauser, L., Yang, L., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0018568 · Cited by 405
Rey, N. L., Steiner, J. A., Maroof, N., Luk, K. C., Madaj, Z., Trojanowski, J. Q., Lee, V. M. ‐., & Brundin, P. (2016) · The Journal of Experimental Medicine · doi:10.1084/jem.20160368 · Cited by 400
Self-citationSheng, Z., Zhang, S., Bustos, D. J., Kleinheinz, T., Pichon, C. E. L., Domínguez, S. L., Solanoy, H. O., Drummond, J., Zhang, X., Ding, X., et al. (2012) · Science Translational Medicine · doi:10.1126/scitranslmed.3004485 · Cited by 358
Li, X., Patel, J. C., Wang, J., Avshalumov, M. V., Nicholson, C., Buxbaum, J. D., Elder, G. A., Rice, M. E., & Yue, Z. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.5604-09.2010 · Cited by 351
Tran, H., Chung, C. H.-Y., Iba, M., Zhang, B., Trojanowski, J. Q., Luk, K. C., & Lee, V. M. ‐. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.05.033 · Cited by 334
Self-citationNovel antibodies to synuclein show abundant striatal pathology in Lewy body diseases
Duda, J. E., Giasson, B. I., Mabon, M. E., Lee, V. M. ‐., & Trojanowski, J. Q. (2002) · Annals of Neurology · doi:10.1002/ana.10279 · Cited by 322
Self-citationOsterberg, V. R., Spinelli, K. J., Weston, L. J., Luk, K. C., Woltjer, R. L., & Unni, V. K. (2015) · Cell Reports · doi:10.1016/j.celrep.2015.01.060 · Cited by 240
Rey, N. L., George, S., Steiner, J. A., Madaj, Z., Luk, K. C., Trojanowski, J. Q., Lee, V. M.-Y., & Brundin, P. (2018) · Acta Neuropathologica · doi:10.1007/s00401-017-1792-9 · Cited by 215
Self-citationChen, C.-Y., Weng, Y.-H., Chien, K.-Y., Lin, K.-J., Yeh, T.-H., Cheng, Y.-P., Lu, C.-S., & Wang, H.-L. (2012) · Cell Death and Differentiation · doi:10.1038/cdd.2012.42 · Cited by 191
LRRK2 modifies α-syn pathology and spread in mouse models and human neurons
Bieri, G., Brahic, M., Bousset, L., Couthouis, J., Kramer, N. J., Ma, R. K., Nakayama, L., Monbureau, M., Defensor, E. B., Schüle, B., et al. (2019) · Acta Neuropathologica · doi:10.1007/s00401-019-01995-0 · Cited by 190
G2019S-LRRK2 Expression Augments -Synuclein Sequestration into Inclusions in Neurons
Volpicelli‐Daley, L. A., Abdelmotilib, H., Liu, Z., Stoyka, L. E., Daher, J. P. L., Milnerwood, A. J., Unni, V. K., Hirst, W. D., Yue, Z., Zhao, H., et al. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.3642-15.2016 · Cited by 185
Penetrance estimate of LRRK2 p.G2019S mutation in individuals of non‐Ashkenazi Jewish ancestry
Lee, A., Wang, Y., Alcalay, R. N., Mejia‐Santana, H., Saunders-Pullman, R. J., Bressman, S., Corvol, J., Brice, A., Lesage, S., Mangone, G., et al. (2017) · Movement Disorders · doi:10.1002/mds.27059 · Cited by 164
Colloquium : Control of dynamics in brain networks
Tang, E., & Bassett, D. S. (2018) · Reviews of Modern Physics · doi:10.1103/revmodphys.90.031003 · Cited by 161
Self-citationProgression in the LRRK2-Associated Parkinson Disease Population
Saunders-Pullman, R. J., Mirelman, A., Alcalay, R. N., Wang, C., Ortega, R. A., Raymond, D., Mejia‐Santana, H., Orbe‐Reilly, M., Johannes, B. A., Thaler, A., et al. (2018) · JAMA Neurology · doi:10.1001/jamaneurol.2017.4019 · Cited by 148
Giaime, E., Tong, Y., Wagner, L. K., Yang, Y. H., Huang, G., & Shen, J. (2017) · Neuron · doi:10.1016/j.neuron.2017.09.036 · Cited by 132
Xiong, Y., Neifert, S., Karuppagounder, S. S., Liu, Q., Stankowski, J. N., Lee, B. D., Ko, H. S., Lee, Y., Grima, J. C., Mao, X., et al. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1712648115 · Cited by 95
G2019S LRRK2 mutation facilitates α-synuclein neuropathology in aged mice
Novello, S., Arcuri, L., Doveró, S., Dutheil, N., Shimshek, D. R., Bézard, E., & Morari, M. (2018) · Neurobiology of Disease · doi:10.1016/j.nbd.2018.08.018 · Cited by 70
Luna, E., & Luk, K. C. (2015) · FEBS Letters · doi:10.1016/j.febslet.2015.10.023 · Cited by 67
Volta, M., & Melrose, H. L. (2017) · Biochemical Society Transactions · doi:10.1042/bst20160238 · Cited by 63
Who was the man who discovered the “Lewy bodies”?
Silva, A. M. R. E., Geldsetzer, F. O., Holdorff, B., KIELHORN, F., Balzer‐Geldsetzer, M., Oertel, W. H., Hurtig, H. H., & Dodel, R. C. (2010) · Movement Disorders · doi:10.1002/mds.22956 · Cited by 58
Elstner, M., Müller, S. K., Leidolt, L., Laub, C., Krieg, L., Schlaudraff, F., Liss, B., Morris, C. M., Turnbull, D. M., Masliah, E., et al. (2011) · Molecular Brain · doi:10.1186/1756-6606-4-43 · Cited by 49
Henderson, M. X., Sengupta, M., McGeary, I., Zhang, B., Olufemi, M. F., Brown, H. J., Trojanowski, J. Q., & Lee, V. M. ‐. (2019) · Acta Neuropathologica Communications · doi:10.1186/s40478-019-0679-5 · Cited by 48
Self-citationRegional levels of physiological α-synuclein are directly associated with Lewy body pathology
Erskine, D., Patterson, L., Alexandris, A. S., Hanson, P. S., McKeith, I. G., Attems, J., & Morris, C. M. (2017) · Acta Neuropathologica · doi:10.1007/s00401-017-1787-6 · Cited by 42
Henderson, M. X., Chung, C. H.-Y., Riddle, D. M., Zhang, B., Gathagan, R. J., Seeholzer, S. H., Trojanowski, J. Q., & Lee, V. M. ‐. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.2705-16.2017 · Cited by 39
Self-citationPredictive Model of Spread of Progressive Supranuclear Palsy Using Directional Network Diffusion
Pandya, S., Mezias, C., & Raj, A. (2017) · Frontiers in Neurology · doi:10.3389/fneur.2017.00692 · Cited by 39
Universal framework for edge controllability of complex networks
Pang, S., Wang, W.-X., Hao, F., & Lai, Y. (2017) · Scientific Reports · doi:10.1038/s41598-017-04463-5 · Cited by 35
Testing the Protein Propagation Hypothesis of Parkinson Disease
Dagher, A., & Zeighami, Y. (2018) · Journal of Experimental Neuroscience · doi:10.1177/1179069518786715 · Cited by 28
Functional and behavioral consequences of Parkinson's disease-associated LRRK2-G2019S mutation
Benson, D. L., Matikainen‐Ankney, B. A., Hussein, A., & Huntley, G. W. (2018) · Biochemical Society Transactions · doi:10.1042/bst20180468 · Cited by 20
Diffusion control in multi-agent networks
Chan, W. H. R., Wildemeersch, M., & Quek, T. Q. S. (2015) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2015.7402872 · Cited by 6
Characterization and Control of Diffusion Processes in Multi-Agent NetworksPreprint
Chan, W. H. R., Wildemeersch, M., & Quek, T. Q. S. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1508.06738 · Cited by 4
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Metadata
- Authors
- Henderson, M. X., Cornblath, E. J., Darwich, A., Zhang, B., Brown, H., Gathagan, R. J., Sandler, R. M., Bassett, D. S., Trojanowski, J. Q., & Lee, V. M. Y.
- Affiliations
- University of Pennsylvania (US)
- Corresponding author
- Henderson, Michael X.
- ORCID
- Venue
- Nature Neuroscience
- Published
- 2019-07-25
- Volume
- 22
- Issue
- 8
- Pages
- 1248-1257
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- PMC
- PMC6662627
- OpenAlex
- W2963495948
- Cited by
- 310
- References
- 55
- Citations by year
- 2026: 33 · 2025: 48 · 2024: 47 · 2023: 35 · 2022: 36 · 2021: 42 · 2020: 54 · 2019: 15
- FWCI
- 24.87
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (5r01ns099348-04)
- National Institute on Aging (U19AG062418, P30AG010124, T32AG000255)
- National Institute of Neurological Disorders and Stroke (P50NS053488, (R01 NS099348)
- Topics
- Health Sciences › Medicine › Clinical Neurology › Parkinson's Disease Mechanisms and Treatments
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- alpha-synuclein pathology, brain connectome, selective neuronal vulnerability, LRRK2 G2019S, neurodegeneration, structural connectivity, network modeling, neuronal cell death, Parkinson's disease
- MeSH terms
- Leucine-Rich Repeat Serine-Threonine Protein Kinase-2, Animals, Brain, Brain Mapping, Female, Male, Mice, Inbred C57BL, Models, Neurological, Neurons, Linear Models, Neural Networks, Computer, Cell Death, Mice, alpha-Synuclein, Connectome
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