Kotredes KP, Pandey RS, Persohn S, Elderidge K, Burton CP, Miner EW, Haynes KA, Santos DF, Williams SP, Heaton N, Ingraham CM, Lloyd C, Garceau D, O'Rourke R, Herrick S, Rangel-Barajas C, Maharjan S, Wang N, Sasner M, Lamb BT, Territo PR, Sukoff Rizzo SJ, Carter GW, Howell GR, Oblak AL. Characterizing Molecular and Synaptic Signatures in mouse models of Late-Onset Alzheimer's Disease Independent of Amyloid and Tau Pathology. bioRxiv. 2023 Dec 20; PubMed.
Recommends
Please login to recommend the paper.
Comments
Aix-Marseille Université
According to Alzforum, there are 204 murine models of AD, showing the complexity of developing a model that mimics AD perfectly. The choice of the best mouse model depends on the specific questions researchers aim to address; there is no universally perfect model. This study emphasizes the effective modeling of predementia stages in mice, often overlooked due to a focus on dramatic changes.
The MODEL-AD initiative leads the creation of innovative mouse models, incorporating humanized genetic risk factors for a more accurate replication of Late-Onset Alzheimer's Disease (LOAD) compared to traditional transgenic models. This recently developed LOAD2 model, featuring APOE4, Trem2*R47H, and humanized Aβ, is a notable addition to this pursuit. In this study, mice were exposed to either a control diet or a high-fat/high-sugar diet (LOAD2+HFD) from the age of 2 months.
By the 18th month, LOAD2+HFD mice exhibited significant cortical neuron loss, elevated insoluble brain Aβ42, increased plasma neurofilament light chain (NfL), and noteworthy alterations in gene/protein expression related to lipid metabolism and synaptic function. In vivo imaging revealed age-dependent reductions in brain region volume and in neurovascular coupling, alongside deficits in acquiring touchscreen-based cognitive tasks.
The comprehensive characterization of LOAD2+HFD mice underscores the model's relevance for preclinical studies targeting LOAD features, independent of amyloid and tau pathologies. The strategic combination of genetic risk factors and dietary stressors provides insights into age-related neurodegeneration, cognitive deficits, and imaging abnormalities, establishing LOAD2+HFD as a valuable resource for investigating AD. The observed age-related neurodegeneration, cognitive deficits, and plasma NfL elevation position LOAD2+HFD as a promising tool for studying predementia phases and identifying therapeutic targets.
However, some considerations emerge when using this model. The absence of tau pathology assessment is a notable limitation, given its significance in AD. While the study doesn't aim to replicate neurofibrillary tangles, evaluating tau phosphorylation could provide a more comprehensive understanding of the model's neuropathological landscape.
The absence of hippocampal-dependent spatial working memory deficit as seen in AD patients raises concerns about the model's representation of primary AD symptoms. Nevertheless, the study's focus on mimicking presymptomatic phases is commendable, addressing a gap in available models.
The drastic reduction in soluble and insoluble Aβ40, coupled with the absence of plaques, challenges the hypothesis that humanized Aβ would favor amyloid pathology, as initially hypothesized by the team. The unexpected findings underscore the complexity of AD pathophysiology and highlight the need for nuanced investigations.
A noteworthy concern is the potential for the observed pathologies in the model to represent obesity-associated neurodegeneration pattern mimicking AD instead of AD pathologies themselves. Indeed, this model, under drastic HFD, induced sustained obesity. Excess weight has been related to brain atrophy and cognitive decline. Reports show that obesity is linked with AD-related changes, such as cerebrovascular damage or Aβ accumulation. Obesity-related gray matter atrophy resembles that of AD; however, those changes are often independent from AD.
Moreover, the variability in markers such as Iba1 and GFAP underscores inter-individual variations. While this mirrors the diversity observed in human AD patients, this variability might create conceptual limitations, particularly in light of evolving European Union directives seeking to strongly reduce in vivo experimentation.
In conclusion, the LOAD2+HFD mouse model offers a promising avenue for investigating LOAD features beyond traditional paradigms. The model's contribution to understanding predementia phases and potential therapeutic targets positions it as a valuable asset in the complex landscape of AD research.
View all comments by Maud GratuzeRIKEN Center for Brain Science
Until a century ago, most people used to die before the age of 50 with few exceptions, suggesting our creator did not expect us to live long enough to suffer from late-onset Alzheimer’s disease (LOAD). Kotredes and colleagues have tried to generate a mouse model of LOAD by combining genetic risk factors, including Apoe4 and TREM2R47H, together with humanization of the mouse Aβ sequence. I think this is a logical approach because Apoe4 and TREM2R47H are the most influential risk factors for LOAD. I expect that humans carrying these genotypes, particularly if homozygous, would be affected by LOAD upon aging with a probability of 100 percent, so such diseased conditions would be equivalent to late-onset familial AD (LOFAD). If mice lived as long as humans, the mutant mice would develop LOAD after some decades.
The question then is, what is the difference between FAD and LOFAD? Neuropathologically, FAD and LOFAD resemble each other in Aβ amyloidosis, neuroinflammation, tau pathology, and neurodegeneration. If these pathological features are the targets for prevention and treatment of AD in both the cases, medications effective for prevention and treatment for FAD should also be effective for LOFAD. If so, preclinical studies would be well done using models of FAD. There is, however, great utility in the LOFAD models. Both the macroscopic and microscopic analyses (spatial transcriptomics and others) would contribute to establishment of cause-and-effect relationships between LOFAD risk factors and AD pathogenesis. I also expect these approaches to contribute to the understanding of the mechanisms underlying these relationships. Because the LOAD model alone does not exhibit the major AD pathologies, it would be interesting to crossbreed them with AppNL-F mouse model.
View all comments by Takaomi SaidoMake a Comment
To make a comment you must login or register.