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Review
. 2019 Jul;28(7):1177-1193.
doi: 10.1002/pro.3606. Epub 2019 Apr 11.

The vexing complexity of the amyloidogenic pathway

Affiliations
Review

The vexing complexity of the amyloidogenic pathway

Manuel A Castro et al. Protein Sci. 2019 Jul.

Abstract

The role of the amyloidogenic pathway in the etiology of Alzheimer's disease (AD), particularly the common sporadic late onset forms of the disease, is controversial. To some degree, this is a consequence of the failure of drug and therapeutic antibody trials based either on targeting the proteases in this pathway or its amyloid end products. Here, we explore the formidable complexity of the biochemistry and cell biology associated with this pathway. For example, we review evidence that the immediate precursor of amyloid-β, the C99 domain of the amyloid precursor protein (APP), may itself be toxic. We also review important new results that appear to finally establish a direct genetic link between mutations in APP and the sporadic forms of AD. Based on the complexity of amyloidogenesis, it seems possible that a major contributor to the failure of related drug trials is that we have an incomplete understanding of this pathway and how it is linked to Alzheimer's pathogenesis. If so, this highlights a need for further characterization of this pathway, not its abandonment.

Keywords: APP-CTF; Alzheimer's disease; Aβ; C99; EOAD; FAD; LOAD; SAD; amyloid; amyloid precursor protein; amyloidogenesis; amyloidogenic; drug trials; etiology; gencDNA; gene; mutants; mutations; neurodegeneration; pathogenesis; plaques; presenilin; therapeutics; variants; variations; α-secretase; β-secretase; γ-secretase.

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Conflict of interest statement

The authors declare that they have no conflicts of interest related to this work.

Figures

Figure 1
Figure 1
Self‐diagnosis by the corresponding author's father of his early symptoms for what proved to be late onset AD. A former mechanical engineer and Korean War era US Air Force cartographer, he succumbed to this disease 10 years later in 2017, at the age of 87.
Figure 2
Figure 2
“Jack plot” illustrating the appearance with aging of biomarkers that now be be measured and used as predictors for the development of AD. The earliest predictor is the detection of long form Aβ in CSF, as collected via a spinal tap. This is followed by the detection of amyloid plaques in the brain through the binding of certain 18F‐labeled compounds and PET. The next predictor is the elevation of the tau protein in CSF and then the detection by magnetic resonance imaging of changes in brain morphology, along with detection by PET of problems with energy metabolism in the brain. Only after these biomarkers appear do early signs of memory loss and other relatively minor problems arise as “mild cognitive impairment”, which finally progresses to full blown AD. While not discussed elsewhere in this review, we suggest a significant additional layer of complexity for the amyloidogenic pathway as a target for AD therapeutics is the fact that Aβ production, deposition, and accumulation takes place over a period of decades. The conundrum of how to target a decades‐long process with a potential therapeutic in a drug trial of short duration represents yet another vexing problem. Figure reproduced with permission from The Lancet Neurology (Elsevier).3
Figure 3
Figure 3
Canonical processing of the amyloid precursor protein. Full‐length APP (either neuronal 751‐ or 695‐residue isoform) is shown in the middle. On the right (red arrows) is the amyloidogenic proteolytic cascade that is initiated by β‐secretase and generates sAPPβ, AICD, and Aβ peptides. On the left (blue arrows) is the nonamyloidogenic proteolysis pathway that is initiated by α‐secretase and generates sAPPα, AICD, and Aα peptides. In both pathways, γ‐secretase cleavage is involved, as shown in light green.
Figure 4
Figure 4
Competing processive γ‐secretase cleavage reaction pathways for the C99 protein. This figure is reproduced with permission from Neurochemical Research (Springer).62
Figure 5
Figure 5
Locations of FAD mutation sites in the presenilin 1 cryo‐EM structure.140 Known FAD disease mutation sites are highlighted in green (WT residue side chains are shown). The magenta protein is a substrate, APP C83, bound to the active site, with the C‐terminal end of its TM domain unraveled in preparation for cleavage.
Figure 6
Figure 6
Model for gencDNA formation and expression in neurons based on work of the Chun lab.177, 178 Illustrated by blue arrows is the canonical gene expression program for neuronal APP splice variants APP‐751 and APP‐695. The gencDNA creation pathway, illustrated by red arrows, is considered to be initiated by APP reverse transcription followed by translocation and recombination back into chromosomal DNA following DNA damage. Newly formed APP gencDNAs can be expressed and fed into the typical gene expression program in blue.

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