Quantitative modelling of amyloidogenic processing and its influence by SORLA in Alzheimer's disease
Open accessAbstract
The extent of proteolytic processing of the amyloid precursor protein (APP) into neurotoxic amyloid-β (Aβ) peptides is central to the pathology of Alzheimer's disease (AD). Accordingly, modifiers that increase Aβ production rates are risk factors in the sporadic form of AD. In a novel systems biology approach, we combined quantitative biochemical studies with mathematical modelling to establish a kinetic model of amyloidogenic processing, and to evaluate the influence by SORLA/SORL1, an inhibitor of APP processing and important genetic risk factor. Contrary to previous hypotheses, our studies demonstrate that secretases represent allosteric enzymes that require cooperativity by APP oligomerization for efficient processing. Cooperativity enables swift adaptive changes in secretase activity with even small alterations in APP concentration. We also show that SORLA prevents APP oligomerization both in cultured cells and in the brain in vivo, eliminating the preferred form of the substrate and causing secretases to switch to a less efficient non-allosteric mode of action. These data represent the first mathematical description of the contribution of genetic risk factors to AD substantiating the relevance of subtle changes in SORLA levels for amyloidogenic processing as proposed for patients carrying SORL1 risk alleles.
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SORL1 underexpression is associated with an increase in Aβ production by blocking redirection of endocytosed APP to the trans-Golgi network.
“SORL1 underexpression has also been associated with an increase in Aβ production by blocking the redirection of endocytosed APP to the trans-Golgi network, which reduces APP processing in endosomes [113, 144, 152].”
From The new genetic landscape of Alzheimer’s disease: from amyloid cascade to genetically driven synaptic failure hypothesis? (2019) · cites this paper as [113]
The ‘Inverse correlation between SORLA activity and APP processing rates’ section reports that lowering SORLA in SH-SY5Y cells is associated with increased Aβ40 production. The cited paper does not establish that this occurs by blocking redirection of endocytosed APP to the trans-Golgi network; its ‘SORLA blocks APP oligomerization and prevents cooperativity in processing’ section instead explains inhibition through SORLA’s interaction with APP. Page numbers are unavailable in our copy. (LLM, conf=0.86)
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Cites
Tight control of gene expression in mammalian cells by tetracycline-responsive promoters.
Gossen, M., & Bujard, H. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.12.5547 · Cited by 4,943 · cited 2× · see citing works
“In the Tet-off version of this system (Gossen and Bujard, 1992), constitutive expression of trans-genes (such as APP and SORLA) is driven from a regulatory site composed of the modified tetracycline-response element (TRE MOD ) and a minimal CMV promoter (Figure 1A).”
Pietrzik, C. U., Busse, T., Merriam, D. E., Weggen, S., & Koo, E. H. (2002) · The EMBO Journal · doi:10.1093/emboj/cdf568 · Cited by 198 · see citing works
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Self-citationDodson, S. E., Andersen, O. M., Karmali, V., Fritz, J. J., Cheng, D., Peng, J., Levey, A. I., Willnow, T. E., & Lah, J. J. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.4582-08.2008 · Cited by 141 · see citing works
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Dourlen, P., Kilinc, D., Malmanche, N., Chapuis, J., & Lambert, J.-C. (2019) · Acta Neuropathologica · doi:10.1007/s00401-019-02004-0 · Cited by 168 · see citing works
More than cholesterol transporters: lipoprotein receptors in CNS function and neurodegeneration
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The Role of SORL1 in Alzheimer’s Disease
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Self-citationSORLA attenuates EphA4 signaling and amyloid β–induced neurodegeneration
Huang, T. Y., Zhao, Y., Jiang, L.-L., Li, X., Liu, Y., Sun, Y., Piña-Crespo, J. C., Zhu, B., Masliah, E., Willnow, T. E., et al. (2017) · Journal of Experimental Medicine · doi:10.1084/jem.20171413 · Cited by 50 · see citing works
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- Authors
- Schmidt, V., Baum, K., Lao, A., Rateitschak, K., Schmitz, Y., Teichmann, A., Wiesner, B., Petersen, C. M., Nykjaer, A., Wolf, J., Wolkenhauer, O., & Willnow, T. E.
- Affiliations
- Max Delbrück Center (DE)
- University of Rostock (DE)
- Leibniz-Forschungsinstitut für Molekulare Pharmakologie (DE)
- Aarhus University (DK)
- Corresponding author
- Willnow, Thomas E
- Venue
- The EMBO Journal
- Published
- 2011-10-11
- Volume
- 31
- Issue
- 1
- Pages
- 187-200
- ISSN
- 0261-4189 (ISSN-L)
- 1460-2075
- PMC
- PMC3252570
- OpenAlex
- W1799481352
- Cited by
- 75
- References
- 4
- Citations by year
- 2025: 3 · 2023: 6 · 2022: 4 · 2021: 1 · 2020: 4 · 2019: 3 · 2018: 3 · 2017: 10 · 2016: 9 · 2015: 7 · 2014: 9 · 2013: 8 · 2012: 8
- FWCI
- 5.16
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Licence
- Locations
- The EMBO Journal (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (submittedVersion)
- Informationszentrum Lebenswissenschaften (ZB MED) (submittedVersion)
- SUNScholar (Stellenbosch University) (submittedVersion)
- Funders
- Bundesministerium für Bildung und Forschung
- Topics
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- Alzheimer's disease, amyloid precursor protein, amyloid-beta, SorLA, SORL1, secretases, amyloidogenic processing, allosteric enzymes, enzyme cooperativity, kinetic modeling, genetic risk factors
- MeSH terms
- Alzheimer Disease, Animals, Cricetinae, Humans, Models, Biological, Amyloid beta-Peptides, CHO Cells, Amyloid beta-Protein Precursor, LDL-Receptor Related Proteins, Membrane Transport Proteins, Amyloid Precursor Protein Secretases
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