. Following spatial Aβ aggregation dynamics in evolving Alzheimer's disease pathology by imaging stable isotope labeling kinetics. Sci Adv. 2021 Jun;7(25) Print 2021 Jun PubMed.

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  1. When, in 1937, John Steinbeck wrote Of Mice and Men, he was drawing on the words of Robert Burns that, “The best laid schemes o' mice an' men/Gang aft a-gley.” In this context, the natural history of Aβ amyloid plaques over 10 weeks in transgenic APP mice has to be cautiously interpreted when being compared to a 20- to 30-year period of Aβ aggregation in human AD. The elegant findings of Michno and colleagues that Aβ1-42 forms the nidus of the mouse plaque and is followed by Aβ1-38 is consistent with what we know about the human condition. But the spread from cortex to hippocampus may not be an exact replica of what is currently being disclosed by longitudinal Aβ-PET studies as people transition from preclinical to prodromal to clinical AD.

    There are so many interesting aspects thrown up by this paper it is difficult to know which should be highlighted. One observation that immediately caught my eye was that “an initial deposition of a small, tetrameric formyl thiophene acid (q-FTAA)-positive” Aβ1-42 core forms the initial deposit. This fits very nicely with our earlier observations that a tetramer (an anti-parallel dimer-dimer) may be at the heart of the aggregation process (Streltsov et al., 2011). But it raises many longstanding questions on how such an oligomer forms and diffuses toward the nidus of a plaque.

    Another observation would be that one would expect a 10-week-old mouse plaque to show substantial post-translational differences from a 20-year-old human plaque. The authors acknowledge this with respect to the ragged N-termini found in the human species, but the apparent relative preservation of the C-terminus (38 vs. 40 vs. 42) remains unexplained. Maybe it is a phenomenon related to the buried C-terminus compared to the exposed N-terminus? Certainly, a very topical issue in the light of aducanumab and other anti-amyloid therapeutic targets.

    The topographic distributions of Aβ plaques in “mice and men” should be different, since the underlying processes are fundamentally different. In humans, the first deposits appear in the precuneus/posterior cingulate/default mode network, for reasons that may be related to the normal function of APP in synaptic plasticity. Involvement of the human hippocampus is a late-stage phenomenon, if it occurs at all. In contrast, the transgenic APP mice are at the mercy of the promoters used to drive expression of the transgene, resulting in a topography that may have little relation to the normal function of APP.

    Finally, it would be nice to see these sophisticated MS-based imaging techniques turned toward the neurofibrillary tangle. Alas, the mice do not respond to the presence of aggregated Aβ in the same way that people do.

    References:

    . Crystal structure of the amyloid-β p3 fragment provides a model for oligomer formation in Alzheimer's disease. J Neurosci. 2011 Jan 26;31(4):1419-26. PubMed.

    View all comments by Colin Masters
  2. As evidence grows for the importance of early intervention in Alzheimer's disease, an understanding of the initial pathogenic processes is essential. Michno and colleagues present iSILK as an auspicious method for following the development and compositional evolution of Aβ plaques in experimental mice. The study is a technical tour de force, and iSILK is a welcome tool for the longitudinal analysis of plaque formation.

    Because the study was performed in a genetically modified mouse model with three different AD-linked mutations in APP, the findings cannot yet be generalized to humans, in whom such multiple mutations don't occur. For instance, the Arctic mutation in humans results in cerebral amyloid angiopathy and ring-like Aβ plaques containing Aβ40 and Aβ42 but lacking a dense core, a pathologic phenotype not fully recapitulated in transgenic mice (e.g., Basun et al., 2008). 

    However, application of the method to different animal models, along with a comparison to related studies of plaques in humans, is likely to yield useful new insights into how plaques emerge, grow, and spread (Wildburger et al., 2018). The approach also might be employed to shed light on the inception of amyloid angiopathy, as well as its variable presence in the AD brain. It could also be informative to extend this general approach to the formation of the cryptic Aβ seeds that precede the appearance of plaques, and thus may be the prime mover of the pathogenic cascade in AD (Uhlmann et al., 2020). 

    References:

    . Clinical and neuropathological features of the arctic APP gene mutation causing early-onset Alzheimer disease. Arch Neurol. 2008 Apr;65(4):499-505. PubMed.

    . Amyloid-β Plaques in Clinical Alzheimer's Disease Brain Incorporate Stable Isotope Tracer In Vivo and Exhibit Nanoscale Heterogeneity. Front Neurol. 2018;9:169. Epub 2018 Mar 22 PubMed.

    . Acute targeting of pre-amyloid seeds in transgenic mice reduces Alzheimer-like pathology later in life. Nat Neurosci. 2020 Dec;23(12):1580-1588. Epub 2020 Nov 16 PubMed.

    View all comments by Lary Walker
  3. I have read this paper with great interest. The molecular (type of Aβ peptides), spatial, and temporal resolution data, as well as the longitudinal information provided by the study, are quite unique.

    The study confirms previous observations, such as the seeding role of Aβ1-42 or the delayed deposition of hippocampal relative to cortical plaques, and provides important insights into early (in vivo) seeding of amyloid and plaque maturation. These early events are considered critical in amyloid pathology, but the mechanisms are poorly understood.

    I find particularly relevant the data about the deposition dynamics of different Aβ peptides across brain regions. In this regard, I would like to note that Aβ1-40 (the major Aβ species generated from wild-type APP) is not produced in the APPNL-G-F mice (due to the presence of the Iberian mutation [APP I716F]). It would be interesting to see if the dynamics of amyloid deposition changes and how it is modified when Aβ1-40 is present in the brain.

    I congratulate the authors for the elegant strategy.

    View all comments by Lucia Chavez-Gutierrez
  4. While the technology for gathering spatial and temporal data is impressive, that data is only as relevant to human AD as this particular mouse model is relevant to human AD—and that remains uncertain, particularly considering the novelty of this model and the fact that it is partly based on the Arctic mutation, which favors oligomeric Aβ over plaques.

    Beyond that, the notion of Aβ1-42 depositing first is in line with descriptions from postmortem human studies decades earlier. It is particularly unclear how important the Aβ1-38 species are in humans compared to Aβ1-40, which seems to play little role in this mouse model. 

    While technically elegant, it is not obvious to me how this study informs new avenues of therapeutic development. That is, agents that prevent accumulation and deposition of Aβ peptides, and/or clearance of oligomeric and fibrillar aggregates once formed, seem as relevant as ever.

    View all comments by William Klunk
  5. Michno et al. follow spatial Aβ aggregation dynamics in the well-established amyloidosis mouse model (APP-KI) which results in early Aβ deposition (Saito et al., 2014). The authors performed metabolic in vivo labeling with stable isotopes (SIL), followed by mass spectrometry imaging to measure SIL kinetics (iSILK) and put forward the hypothesis that Aβ pathology starts with the formation of dense-core Aβ42 deposits, followed by deposition of shorter Aβ38 peptides. We recently compared this APP-KI mouse line with the overexpression amyloidosis model APPPS1 (Radde et al., 2006) for their Aβ pathology and microglial proteomic profiles and were surprised to see the reduced levels of Thiazin red positive fibrillar Aβ (fibrillar cores) in the APP-KI model while diffuse Aβ material could be readily detected a lot earlier (Sebastian Monasor et al., 2020). We also verified this finding using the LCO probes (Sebastian Monasor et al., 2020) and PET imaging (Biechele et al., 2021). Thus, it would have been an advantage to also perform iSILK experiments in a model with a higher fibrillar Aβ content such as APPPS1. Exploring additional mouse models would also allow for generalization of the presented findings.

    Noteworthy, it remains questionable whether fibrillar and more diffuse plaques actually follow the same evolutionary path. Fibrillar plaques are often more prominent in later stages of AD and diffuse plaques are often referred to as immature plaques and such morphologies—lacking the fibrillar core—exist in AD brains (Walker, 2020). Translation of plaque morphologies from mouse to human is definitely not 1:1, but eventually we would like to know that what is observed in mouse models can be of relevance for human pathology. Moreover, we need to be cautious in interpreting diffuse deposits as something beneficial and dense core deposits as something detrimental. This very important issue remains controversial.

    A surprising result of the report is the association of Aβ38 with amyloid plaques much later than the early seeding Aβ42. This aspect is intriguing because the occurrence of Aβ38 is most likely linked to the presence of the Arctic mutation in this model, which was previously associated with Aβ38 deposition, primarily found in cerebral amyloid angiopathy (Moro et al., 2012). Of note, we detected Aβ38 also in the fibrillar core of Aβ plaques in the APP-KI mice (unpublished data), and the dynamics of the Aβ38 deposition should be further addressed by immunohistochemical and biochemical studies at different pathological stages. In addition, it should also be considered that the on-off diffusion and the half-life of Aβ could be variable for different Aβ species.

    Overall, elucidating plaque composition and their spatial distribution in the brain is highly relevant. Despite the technical limitations that may still have to be overcome with this technology, it is important to further develop this area of research. In particular, this technology may be helpful for the studies of amyloid plaques upon genetic modifications of microglial regulators as some of them (such as Trem2 or ApoE) contribute to changes in the amyloid plaque conformation (Biechele et al., 2021; Parhizkar et al., 2019). 

    Furthermore, this information may be relevant for the judgment of the amyloid plaque load upon Aβ immunotherapy as different antibodies may preferentially target and induce phagocytic clearance of denser fibrillar material while others may target more soluble (protofibrillar and oligomeric) Aβ species. Additionally, as already anticipated in this manuscript, the various familial AD mutations produce different Aβ species and iSILK technology may help in revealing Aβ diversity and their tissue distribution and facilitate our understanding of the underlying pathologies.

    References:

    . Glitter in the Darkness? Non-fibrillar β-amyloid Plaque Components Significantly Impact the β-amyloid PET Signal in Mouse Models of Alzheimer's Disease. J Nucl Med. 2021 May 20; PubMed.

    . APP mutations in the Aβ coding region are associated with abundant cerebral deposition of Aβ38. Acta Neuropathol. 2012 Dec;124(6):809-21. PubMed.

    . Loss of TREM2 function increases amyloid seeding but reduces plaque-associated ApoE. Nat Neurosci. 2019 Feb;22(2):191-204. Epub 2019 Jan 7 PubMed.

    . Abeta42-driven cerebral amyloidosis in transgenic mice reveals early and robust pathology. EMBO Rep. 2006 Sep;7(9):940-6. PubMed.

    . Single App knock-in mouse models of Alzheimer's disease. Nat Neurosci. 2014 May;17(5):661-3. Epub 2014 Apr 13 PubMed.

    . Fibrillar Aβ triggers microglial proteome alterations and dysfunction in Alzheimer mouse models. Elife. 2020 Jun 8;9 PubMed.

    . Aβ Plaques. Free Neuropathol. 2020;1 Epub 2020 Oct 30 PubMed.

    View all comments by Michael Willem
  6. Molecular-specific maps of Aβ plaque formation in mouse brains represent an impressive demonstration of recent advances in imaging mass spectrometry. While it is unclear that the approach currently has the necessary sensitivity to detect plaques in human samples, the method described provides a wealth of complementary information to classical neuroimaging methods.

    In the future, imaging mass spectrometry may provide scientists with a detailed view of the location and interaction between plaque molecules and an array of experimental drug treatments.

    View all comments by Nathan Yates

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