19 Sep 2024

Alzheimer’s is a multifaceted disease, particularly in its sporadic, late-onset form. Myriad factors—genetics, environment, cardiovascular health, metabolism, and inflammation—contribute to a decades-long process. Generating animal models that accurately reflect this neurodegenerative train wreck is a tall order, but scientists have long wanted to move beyond the flawed overexpression mice that they have relied upon for years. Funded by the National Institute on Aging in 2016, the MODEL-AD consortium rose to meet this challenge. Since then, scientists at Indiana University in Indianapolis, the University of Pittsburgh in Pennsylvania, The Jackson Laboratory in Bar Harbor, Maine, the biomedical research nonprofit Sage Bionetworks in Seattle, and University of California, Irvine, have used human datasets to guide development of dozens of mouse models of late-onset AD. Of the 80 strains made by consortium scientists so far, 74 are available to order, and colonies of six others are still being raised. Meanwhile, more than a dozen others are being developed.

Some express humanized versions of Aβ and tau, others express AD risk variants in ApoE, TREM2, and many other genes identified in GWAS and exome sequencing studies. Scientists can use these lines not only to study disease mechanisms, but also to test emerging therapeutics in preclinical pipelines.

Consortium scientists are eager for the field to start using models that more accurately capture the underlying biology of AD, Adrian Oblak of Indiana University told Alzforum. She co-leads that institution’s MODEL-AD core along with Bruce Lamb.

MODEL-AD aims to create mouse models that reflect different biological subtypes of AD that have been found in people, in hopes of improving drug discovery and tailoring treatments to different forms of AD (Jan 2021 news; Dec 2023 news). In 2022, Alzforum reported that some of the new models displayed subtler, potentially more translatable, phenotypes than mice overexpressing APP and PS1 genes saddled with familial AD mutations (Nov 2022 news). Since then, MODEL-AD has generated and characterized more models. Researchers presented the newest findings at AAIC in Philadelphia last July and in a coordinated special issue of Alzheimer’s & Dementia.

Just how well are these models catching on in the research community? Between 2018 and July of this year, 88 studies using MODEL-AD mice were logged into the Mouse Genome Informatics database, a number that is likely an underestimate, Jackson Lab’s Michael Sasner told Alzforum. Nevertheless, this pales in comparison to the number of studies using classic overexpression amyloidosis models introduced just after the turn of the century. PubMed identified 1,122 studies using the 5xFAD mouse strain alone since 2018, while 2,034 studies used APP/PS1 mice and 548 used 3xTg.

Still, Sasner expects more studies with MODEL-AD mice to come down the pike soon. Most of those published so far have used the ApoE and TREM2 models that were created in the early years of the consortium, but more recently, requests for new models, particularly those carrying a combination of AD risk variants, have risen substantially, Sasner said. While Jackson Labs, which is a nonprofit research institute, fielded orders for 500 MODEL-AD mice in 2018, that number had quadrupled by 2022, and more than 2,000 have already been ordered in 2024. Academic labs were the first to start using the mice, but now more than half go to biotech/pharma companies, he said.

Sasner pointed out that switching to a new mouse strain, let alone publishing the findings, is neither straightforward nor quick, since researchers have to phase out the strains they’re already working with, and rear new mice until they are old enough for AD-related experiments. Sasner said that older mice may become available for some of the strains.

Several of the new models—for example, LOAD1 and LOAD2 strains—are curated in Alzforum’s research model database, with more to be added soon.

LOADed with Variants
How well do these new models mimic late-onset AD? In Philadelphia, Oblak presented synaptic findings on LOAD2 mice. This triple mutant line carries two copies of humanized APOE4, the R47H AD risk variant in the endogenous mouse Trem2, and a humanized Aβ sequence within the mouse APP gene.

This strain is one of three late-onset AD “base models” generated by the IU MODEL-AD center. The others are LOAD1, which carries humanized ApoE4 and R47H-TREM2, and the newer LOAD3, which carries humanized APP and ApoE4 along with a humanized tau gene of the H1 haplotype. This strain is still being bred to sufficient numbers, and is not yet available .

Previously, Oblak had reported that by 18 months of age, LOAD2 mice had no amyloid plaques, mildly activated microglia and astrocytes, and barely any neuronal loss. However, LOAD2 mice fed high-fat chow that mimics the cardiovascular stress provoked by a typical Western diet did lose a small but significant number of neurons. This tracked with elevated plasma NfL, a marker of neuronal damage, and flagging performance on touch screen-based mouse memory tests (Jan 2024 news).

At AAIC, more synaptic snafus emerged. In collaboration with Nick Seyfried’s lab at Emory University in Atlanta, the Oblak lab compared the proteomic signatures of LOAD2 mouse brains with previously identified AD signatures (Feb 2022 news). Similar modules of dysregulated proteins correlated with disease in both. For example, among 95 post-synaptic proteins, the same ones were downregulated in LOAD2 mice and in people with AD. These disease-related correlations were strongest in mice on a high fat diet, but were still significant in those fed normal chow.

In further experiments with LOAD2 mice fed a regular diet, both the post-synaptic marker PSD95 and the pre-synaptic marker SV2A were dramatically reduced in hemi-brain extracts of 12-month-old LOAD2 mice relative to controls. However, when Oblak zoomed in on synapses, she was surprised to find that the LOAD2 terminals had almost twice as much SV2A as did control synapses. This could suggest a compensatory uptick in synaptic signaling, she told Alzforum. Possibly supporting this interpretation: the composition of receptor subunits within both NMDA and AMPA receptors was skewed in the LOAD2 mice. Their NMDA receptors contained more NR2B subunit, which is known to promote pro-apoptotic signaling, whereas their AMPA receptors contained a glut of GluA2 relative to GluA1 subunits, a shift that might lead to excitotoxicity, Oblak suggested.

Microglia seemed to have taken notice of these synaptic imbalances. In 18-month-old LOAD2 mice, Oblak found a dramatic uptick in microglia loaded up with synaptic material.

These synaptic changes appeared to have functional consequences. While control mice demonstrated a dip in long term potentiation—a measure of synaptic plasticity—with age, LOAD2 mice already had weak LTP at four months, which stayed low as they got older.

“Overall, these changes imply a reorganization of excitatory synaptic transmission in the absence of amyloid and tau pathologies,” Oblak said. She believes these mice model the inflammatory and synaptic problems that occur in the early stages of AD, before Aβ and tau pathology have inundated the brain, and invites labs across the field to use them.

Besides the LOAD 1 to 3 models, scientists led by Michael Koob at the University of Minnesota have generated “genome replacement” mice, in which they swap an entire mouse gene and its surrounding regulatory regions for the human version (Benzow et al., 2024). GR mice carry different ApoE alleles, MAPT haplotypes, and α-synuclein (for current list, see https://www.jax.org/research-and-faculty/resources/model-ad-consortium/models-available/gene-replacement-models). Several of these models are described in Alzforum’s research model database (MAPT(H1.0)-GR; MAPT (H1.0*N279K)-GR; MAPT(H2.1)-GR; MAPT(H1.0*)P301L-GR; and MAPT 10IVS+16 C>T). Some of these are available for study now, others will be within the next year.

Piling On More Risk
At AAIC, Jackson Lab’s Gregory Carter laid out current developments in using CRISPR to plant AD risk variants into LOAD1, and, more recently, the LOAD2 background. Previously, Carter and colleagues had reported 11 new mouse strains expressing coding variants in 11 different genes (image below and Sasner et al., 2024). The scientists used transcriptomics to compare how these variants affected biological pathways tied to AD in the AMP-AD cohort (Wan et al., 2020). They found, for example, that the A1527G variant in ABCA7 provoked expression changes in groups of genes involved in immune responses, cell cycle, myelination, and cellular stress responses, which corresponded to AD-related modules found in people. On the other hand, variants in SORL1 and PLCG2 genes skewed modules of neuron-related pathways.

Added Risk. Coding risk variants were introduced into LOAD1 mice, which already carry ApoE4 and TREM2-R47H risk alleles. [Courtesy of Sasner et al., 2024.]

Carter chose these variants based on five criteria: how well the wild-type allele is conserved between people and mice, predicted pathogenicity, well-replicated association findings, how common the variants are, and predicted biological function (image below). He included the last so the scientists would generate models for a variety of pathways involved in LOAD. Jackson Lab’s Sasner described this initial batch of coding variants as “low-hanging fruit,” in that there was little ambiguity about the identity of the causal risk gene, and the effect each variant likely had in mice and in people.

To Model, or Not? Starting with coding (C) and noncoding (NC) AD risk variants identified in human studies (top), scientists used five criteria (left) to predict if variants would behave in mice as in people. Those that met all five were CRISPRed into LOAD2 mice. [Courtesy of Gregory Carter, Jackson Lab.]

Carter used the same criteria to select which noncoding variants to model. Most GWAS hits reside in promoters, enhancers, and introns, from where they typically influence expression of nearby genes. Because human and mouse cells can regulate gene expression quite differently, it is trickier to model the effects of noncoding variants. What’s more, often it’s not even clear which gene is affected. Consequently few of these variants pass all of five criteria.

At AAIC, Carter showcased nine variant lines that made the cut (image below). Five have a single-nucleotide polymorphism in a promoter, enhancer, or intron of BIN1, CD2AP, EPHA1, PTK2B, SCIMP. One lacks a 2kb enhancer near the microglial ADAMts4 gene. Another has had the third exon in the IL1-RAP gene removed to mimic the effect of a SNP in a non-conserved intron in the human ortholog. This second batch also included two coding variants—the D57N missense mutation in PTPRB, and the Y213 stop-gain variant in IL-34. All these risk variants were introduced into the LOAD2 line and are available from Jackson Labs.

Beyond Coding. A new batch of mouse strains, on the LOAD2 background, carry noncoding AD risk variants introduced into promoters, enhancers, and introns. [Courtesy of Greg Carter, Jackson Lab.]

Once these mice were 1 year old, the researchers compared their transcriptomes with those of LOAD2 controls and human postmortem brain samples from the AMP-AD cohort. Focusing on 19 “biodomains”—biological processes such as immune response, synaptic function, lipid metabolism, mitochondrial function, APP processing, and apoptosis—they pinpointed pathways specifically influenced by each variant. For example, they found that the EphA1 variant dramatically altered genes involved in apoptosis, while the PTRB variant skewed expression of genes involved in APP metabolism—specifically, those related to Aβ clearance.

These new mouse strains move consortium scientists closer to their overall goal of creating a catalog of models that affect specific disease-related biological pathways, Carter said. “If you have a targeted therapeutic that you would like to test in vivo, we can then match the most suitable mouse models with that candidate,” he added.

Scientists from academia or biotech can purchase mice from Jackson Labs to run this type of testing on their own. Or they can have their candidate therapeutic tested in the NIA-funded preclinical testing core that is part of MODEL-AD. Led by Paul Territo at Indiana University and Stacey Rizzo at the University of Pittsburgh, the core evaluates selected drug candidates for pharmacokinetics and dynamics, in-vivo target engagement in relevant disease models, cognitive/behavioral effects, and potential disease-modification. As a proof of concept, they have applied their testing pipeline to drugs that have already gone through clinical trials, including the BACE1 inhibitor verubecestat and the anti-seizure drug levetiracetam (Oblak et al., 2022; Onos et al., 2022).

Interested? Investigators can apply via the STOP-AD Compound Submission Portal. A steering committee selects promising compounds, considering both the available mechanistic data in support of the drug, and how well it pairs with MODEL-AD mouse strains. At AAIC, Territo said they plan to put one or two compounds through this process per year. Sasner told Alzforum that about 10 drugs are already in the pipeline, though he would not disclose what they are. Once testing is complete, compounds, sponsors, and all data will be openly available, he said.

Modeling Protection
At the University of California, Irvine, another MODEL-AD center headed by Frank LaFerla, Andrea Tenner, and Kim Green, has produced its own batch of mice. Their menagerie includes human Aβ knock-ins, human tau knock-ins, and strains harboring both coding and non-coding AD risk variants (image below). In Philadelphia, Green presented findings from two of these. One carries a coding variant in the gene for the ABCA7 membrane transporter, while the other has the R154S Christchurch variant (aka R136S) in mouse ApoE.

More Risk Variants. UCI has “platform lines” that model Aβ and tau pathology, as well as lines incorporating AD risk variants. [Courtesy of Kim Green, UCI.]

The human ABCA7 variant is a V1599M mutation that came up in exome sequencing and is predicted to be deleterious. However, because it is so rare, it has been impossible thus far to definitively tie it to AD risk, Green told Alzforum. Using CRISPR-Cas9, the scientists introduced the corresponding mouse mutation, V1613M, into both copies of the mouse gene.

First author Claire Butler and colleagues wanted to know how this variant would affect amyloid plaques, so they initially crossed the V1613M strain to 5xFAD mice. The offspring reduced plaque load, dystrophic neurites, and plasma NfL. This was unexpected, Green said, because ABCA7 deficiency increases plaques. Rather than loss of function, the findings imply that this ABCA7 variant causes a protective gain of function. A recent paper tied this protection to reduced Aβ production brought about by altered APP trafficking (Butler et al., 2024).

Green said they are introducing the ABCA7-V1613M mutation into MODEL-AD humanized Aβ knock-in strains. This will teach them how it behaves under more physiological levels of pathology; 5xFAD mice overexpress mutant APP and produce copious amounts of Aβ.

While the protective effect of ABCA7-V1613M came as a surprise, the ApoE Christchurch mutation is well-known for fending off Aβ-induced tau pathology, and cognitive decline, in a carrier of the highly pathogenic Paisa mutation in presenilin-1 (Sep 2022 conference news). To try to understand this, Green used CRISPR to introduce the variant into the mouse ApoE gene, and crossed these ApoE-Ch mice to 5xFAD and to PS19 f tauopathy mice. Graduate student Kristine Tran and colleagues found that ApoE-Ch assuaged plaques in the former, but not tau pathology in the latter.

What is going on at the cellular level here? The scientists used single-cell and spatial transcriptomics to investigate the transcriptional state of microglia and astrocytes adjacent to Aβ plaques or tau-laden neurons. Essentially, they found that the Christchurch variant promoted microglia to adopt a disease-associated signature (DAM) around plaques (Jun 2017 news). In contrast, the variant put the kibosh on this DAM response in PS19 mice, and dampened a disease-associated astrocyte signature as well (Jan 2017 news; Habib et al., 2020).

The findings are reported in a preprint on BioRxiv (Tran et al., 2024). They jibe with previous studies implying DAM responses are beneficial in the context of amyloid, but harmful in the context of tau pathology. By promoting the former and inhibiting the latter, ApoE-Ch bolsters “good” microglial responses while scuppering the “bad” ones, Green suggested.

Situational Switch. The ApoE-Ch variant enhances (red arrows) disease-associated signatures around Aβ plaques (left), but restrains them (blue arrows) in the presence of tau aggregates (right).

Exactly how Christchurch tailors microglial responses depending on the pathological environment is the next question, Green told Alzforum. He thinks that more than any other discovery, this ApoE variant could point the way to therapeutics that promote beneficial glial responses to AD pathology, regardless of disease stage.

The findings dovetail with those reported from other ApoE-Ch mouse models of amyloidosis and tau pathology (Dec 2023 news). These ApoE-Ch mice are being crossed with humanized Aβ and tau knock-in models to study the effects of the variant in a more physiological context.—Jessica Shugart

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References

News Citations

1. Expression Analysis Uncovers Three Distinct Forms of Alzheimer’s 14 Jan 2021
2. And Then There Were Five: CSF Proteomics Defines Alzheimer’s Subtypes 7 Dec 2023
3. Cornucopia: LOADs of New Mouse Models Available 5 Nov 2022
4. Mouse Model LOADs on the Risk Factors 19 Jan 2024
5. Proteomics Highlight Alzheimer’s Changes in Matrisome, MAPK Signaling 3 Feb 2022
6. In Brain With Christchurch Mutation, More ApoE3 Means Fewer Tangles 7 Sep 2022
7. Hot DAM: Specific Microglia Engulf Plaques 9 Jun 2017
8. Microglia Give Astrocytes License to Kill 20 Jan 2017
9. APOE Christchurch Variant Tames Tangles and Gliosis in Mice 17 Dec 2023

Research Models Citations

1. 5xFAD (B6SJL)
2. APPPS1
3. 3xTg
4. Trem2 R47H KI x APOE4 (LOAD1)
5. hAbeta/APOE4/Trem2*R47H (LOAD2)
6. MAPT(H1.0)-GR
7. MAPT(H1.0*N279K)-GR
8. MAPT(H2.1)-GR
9. MAPT(H1.0*)P301L-GR
10. MAPT 10IVS+16 C>T

Mutations Citations

1. APOE C130R (ApoE4)
2. TREM2 R47H
3. APOE R154S (Christchurch)
4. PSEN1 E280A (Paisa)

Therapeutics Citations

1. Verubecestat
2. AGB101

Paper Citations

1. Benzow K, Karanjeet K, Oblak AL, Carter GW, Sasner M, Koob MD. Gene replacement-Alzheimer's disease (GR-AD): Modeling the genetics of human dementias in mice. Alzheimers Dement. 2024 Apr;20(4):3080-3087. Epub 2024 Feb 11 PubMed.
2. Sasner M, Preuss C, Pandey RS, Uyar A, Garceau D, Kotredes KP, Williams H, Oblak AL, Lin PB, Perkins B, Soni D, Ingraham C, Lee-Gosselin A, Lamb BT, Howell GR, Carter GW. In vivo validation of late-onset Alzheimer's disease genetic risk factors. Alzheimers Dement. 2024 Jul;20(7):4970-4984. Epub 2024 Apr 30 PubMed.
3. Wan YW, Al-Ouran R, Mangleburg CG, Perumal TM, Lee TV, Allison K, Swarup V, Funk CC, Gaiteri C, Allen M, Wang M, Neuner SM, Kaczorowski CC, Philip VM, Howell GR, Martini-Stoica H, Zheng H, Mei H, Zhong X, Kim JW, Dawson VL, Dawson TM, Pao PC, Tsai LH, Haure-Mirande JV, Ehrlich ME, Chakrabarty P, Levites Y, Wang X, Dammer EB, Srivastava G, Mukherjee S, Sieberts SK, Omberg L, Dang KD, Eddy JA, Snyder P, Chae Y, Amberkar S, Wei W, Hide W, Preuss C, Ergun A, Ebert PJ, Airey DC, Mostafavi S, Yu L, Klein HU, Accelerating Medicines Partnership-Alzheimer’s Disease Consortium, Carter GW, Collier DA, Golde TE, Levey AI, Bennett DA, Estrada K, Townsend TM, Zhang B, Schadt E, De Jager PL, Price ND, Ertekin-Taner N, Liu Z, Shulman JM, Mangravite LM, Logsdon BA. Meta-Analysis of the Alzheimer's Disease Human Brain Transcriptome and Functional Dissection in Mouse Models. Cell Rep. 2020 Jul 14;32(2):107908. PubMed.
4. Oblak AL, Cope ZA, Quinney SK, Pandey RS, Biesdorf C, Masters AR, Onos KD, Haynes L, Keezer KJ, Meyer JA, Peters JS, Persohn SA, Bedwell AA, Eldridge K, Speedy R, Little G, Williams SP, Noarbe B, Obenaus A, Sasner M, Howell GR, Carter GW, Williams H, Lamb BT, Territo PR, Sukoff Rizzo SJ. Prophylactic evaluation of verubecestat on disease- and symptom-modifying effects in 5XFAD mice. Alzheimers Dement (N Y). 2022;8(1):e12317. Epub 2022 Jul 14 PubMed.
5. Onos KD, Quinney SK, Jones DR, Masters AR, Pandey R, Keezer KJ, Biesdorf C, Metzger IF, Meyers JA, Peters J, Persohn SC, McCarthy BP, Bedwell AA, Figueiredo LL, Cope ZA, Sasner M, Howell GR, Williams HM, Oblak AL, Lamb BT, Carter GW, Rizzo SJ, Territo PR. Pharmacokinetic, pharmacodynamic, and transcriptomic analysis of chronic levetiracetam treatment in 5XFAD mice: A MODEL-AD preclinical testing core study. Alzheimers Dement (N Y). 2022;8(1):e12329. Epub 2022 Aug 23 PubMed.
6. Butler CA, Mendoza Arvilla A, Milinkeviciute G, Da Cunha C, Kawauchi S, Rezaie N, Liang HY, Javonillo D, Thach A, Wang S, Collins S, Walker A, Shi KX, Neumann J, Gomez-Arboledas A, Henningfield CM, Hohsfield LA, Mapstone M, Tenner AJ, LaFerla FM, Mortazavi A, MacGregor GR, Green KN. The Abca7V1613M variant reduces Aβ generation, plaque load, and neuronal damage. Alzheimers Dement. 2024 Jul;20(7):4914-4934. Epub 2024 Mar 20 PubMed.
7. Habib N, McCabe C, Medina S, Varshavsky M, Kitsberg D, Dvir-Szternfeld R, Green G, Dionne D, Nguyen L, Marshall JL, Chen F, Zhang F, Kaplan T, Regev A, Schwartz M. Disease-associated astrocytes in Alzheimer's disease and aging. Nat Neurosci. 2020 Jun;23(6):701-706. Epub 2020 Apr 27 PubMed.
8. Tran KM, Kwang N, Gomez-Arboledas A, Kawauchi S, Mar C, Chao D, DaCunha C, Wang S, Collins S, Walker A, Shi K-X, Alcantara JA, Neumann J, Tenner AJ, LaFerla FM, Hohsfield LA, Swarup V, MacGregor GR, Green KN. APOE Christchurch enhances a disease-associated microglial response to plaque but suppresses response to tau pathology. 2024 Jun 04 10.1101/2024.06.03.597211 (version 1) bioRxiv.

External Citations

1. MODEL-AD
2. Alzheimer’s & Dementia
3. https://www.jax.org/research-and-faculty/resources/model-ad-consortium/models-available/gene-replacement-models
4. preclinical testing core
5. STOP-AD Compound Submission Porta

Further Reading

No Available Further Reading