Abstract Background Numerous AD risk loci and variants have been identified by large‐scale genetic studies, but few have been functionally verified and models to study their mechanism of action are lacking. The Model Organism Development and Evaluation for Late‐onset AD (MODEL‐AD) Center was created to develop, characterize, and distribute more precise preclinical models for late‐onset AD (LOAD) by engineering these disease‐associated variants into mouse models, and characterizing the resulting phenotypes using clinically relevant assays. Method Diverse criteria including replication in multiple studies, predicted pathogenicity of variant, sequence conservation between human and mouse, and expression in relevant cell types were used to prioritize risk variants, which were then engineered into a mouse model that expresses the AD risk variants APOE4 and Trem2*R47H. Primary screening was done by transcriptomic analysis using the nanoString Mouse AD Panel at 4, 8, and 12 months. Result Bioinformatics studies enabled us to prioritize coding variants in the Abca7, Clasp2, Mthfr, Mtmr4, Plcg2, Shc2, Slc6a17, Snx1, and Sorl1 loci. Knockouts of Abca7 , Ceacam1 , Il1rap , and Plcg2 have also been created to model human loss of function variants. Transcriptomic analysis demonstrated that the Abca7*A1527G and Mthfr*C677T models exhibited some age‐dependent similarities to transcriptomic changes seen in post‐mortem samples from the AMP‐AD cohort. These will move on to deep phenotyping out to 24 months of age. Analysis of other models are still in progress and will be presented. Humanized APP and Tau ( MAPT ) models are also in progress. Conclusion We have prioritized Abca7*A1527G and Mthfr*C677T models to be comprehensively characterized up to 24 months of age in the MODEL‐AD program. We will discuss our approach to prioritize genetic variants, develop novel models relevant to LOAD, and use clinically relevant measures to determine which models are most useful for translational studies. All models are made available for both academic and for‐profit use from The Jackson Laboratory, and all validation data will be shared via the AMP‐AD knowledge portal. For more information see www.model‐ad.org.
Abstract Background Late‐onset Alzheimer’s disease (LOAD) is the most common form of dementia without an approved therapy. Transgenic overexpression animal models do not effectively produce the heterogeneity observed clinically in LOAD patients and thus are not ideal for therapy development. Hence, the Model Organism Development and Evaluation for Late‐onset AD (MODEL‐AD) Center is developing, characterizing, and distributing novel mouse models expressing humanized, clinically relevant risk factors. Analysis of aging LOAD2 mice that better phenocopy human disease will inform the further development of subsequent generations of models and reveal more appropriate molecular targets useful in the treatment of LOAD. Method Two risk factors of LOAD, APOEe4 and Trem2 * R47H, were incorporated into C57BL/6J mice along with humanized amyloid‐beta to produce the LOAD2 model. Mice were aged up to 24 months. In some mice, high‐fat diet replaced normal mouse chow. An animal phenotyping pipeline was employed to qualify and align with neurodegenerative disease states and phenotypes observed in human patients. In vivo imaging in addition to behavior and wellness assays were performed, as were analyses of blood and brain tissue for risk‐factor‐related alterations in neuropathology, transcriptomics, metabolomics, and proteomics. Result Aged LOAD2 mice on high‐fat diet present altered cytokine profiles in the brain, and peripherally, however no overt hippocampal pathology nor differences in long‐term potentiation were observed. Expression of human amyloid did not yield plaque formation in 18‐month mice. High‐fat diet was a strong determinant during behavioral phenotyping. Correlation of transcriptional profiling with human AMP‐AD modules determined individual and synergistic effects between genetic and environmental risk factors compared to human data. Continuing efforts to dissect the clinically‐relevant downstream effects of sex, age, genotype, and diet in these animals remain. Conclusion The MODEL‐AD consortium has established the LOAD2 mouse model to study the effects of genetic and environmental risk factors of LOAD. This strain serves as a platform for the incorporation of additional AD risk factors (both genetic and environmental) to more closely align phenotypes in the mouse to outcomes observed in the clinic. Here we show the evidence of emerging disease pathology in an animal model exposed to genetic and environmental risk factors.
Subcritical epileptiform activity is associated with impaired cognitive function and is commonly seen in patients with Alzheimer's disease (AD). The anti-convulsant, levetiracetam (LEV), is currently being evaluated in clinical trials for its ability to reduce epileptiform activity and improve cognitive function in AD. The purpose of the current study was to apply pharmacokinetics (PK), network analysis of medical imaging, gene transcriptomics, and PK/PD modeling to a cohort of amyloidogenic mice to establish how LEV restores or drives alterations in the brain networks of mice in a dose-dependent basis using the rigorous preclinical pipeline of the MODEL-AD Preclinical Testing Core.
Abstract Background The Model Organism Development and Evaluation for Late‐onset AD (MODEL‐AD) Consortium was established to generate and characterize more translatable animal models for late‐onset Alzheimer’s disease (LOAD) based on human genetic risk variants. While numerous genetic risk loci for LOAD have been identified, few have been experimentally verified in vivo and in many cases the risk variants have not been validated. The development of new models incorporating LOAD genetic risk should improve our understanding of disease mechanisms and improve preclinical testing of potential therapeutics. Method Coding and non‐coding LOAD risk variants were prioritized based on human data sets, with the goal of targeting diverse pathways (e.g., neuroinflammation, vascular risk, metabolic function, lipid homeostasis). Risk variants in Abca7, Adamts4, Bin1, Erc2, Mthfr, Mtmr4, Plcg2, Ptk2b, Slc6a17, Snx1, Sorl1 and other loci were engineered into mouse models expressing humanized APOE4 and the Trem2*R47H risk variant; in more recent models, a humanized Abeta allele was also included. A novel transcriptomic panel, based on clinical LOAD samples (Preuss et al, 2020) was used to evaluate how well each model replicated clinical transcriptomic changes with disease. Models were aligned to ROSMAP clinical subtypes. Result We have identified specific human AD‐related pathways disrupted in an age‐dependent manner in these novel mouse models. Specifically, mouse models carrying human AD risk variants Abca7*A1527G, Mthfr*C677T , and Plcg2*M28L exhibited transcriptomics changes similar to those seen in LOAD patients. Most models could be readily matched to either the inflammatory or non‐inflammatory subtype. Conclusion We have prioritized mouse models expressing LOAD risk variants in Abca7 , Mthfr , and Plcg2 for comprehensive phenotyping using clinically relevant measures including transcriptomics and proteomics, biomarkers, neuropathology and in vivo imaging at advanced ages (24 months). Ongoing projects will use human data to guide how to combine alleles to create models that match multi‐omic signatures of AD subtypes and test the effects of environmental risk factors such as high‐fat diet. Through this effort we aim to develop improved models for testing targeted therapeutics.
Identification of horizontal gene transfers (HGTs) has primarily relied on phylogenetic tree based methods, which require a rich sampling of sequenced genomes to ensure a reliable inference. Because the success of phylogenetic approaches depends on the breadth and depth of the database, researchers usually apply stringent filters to detect only the most likely gene transfers in the genomes of interest. One such study focused on a highly conservative estimate of trans-domain gene transfers in the extremophile eukaryote, Galdieria sulphuraria (Galdieri) Merola (Rhodophyta), by applying multiple filters in their phylogenetic pipeline. This led to the identification of 75 inter-domain acquisitions from Bacteria or Archaea. Because of the evolutionary, ecological, and potential biotechnological significance of foreign genes in algae, alternative approaches and pipelines complementing phylogenetics are needed for a more comprehensive assessment of HGT. We present here a novel pipeline that uncovered 17 novel foreign genes of prokaryotic origin in G. sulphuraria, results that are supported by multiple lines of evidence including composition-based, comparative data, and phylogenetics. These genes encode a variety of potentially adaptive functions, from metabolite transport to DNA repair.
Abstract Background Hyperphosphorylation and intraneuronal aggregation of the microtubule-associated protein tau is a major pathological hallmark of Alzheimer’s disease (AD) brain. Of special interest is the effect of cerebral amyloid beta deposition, the second main hallmark of AD, on human tau pathology. Therefore, studying the influence of cerebral amyloidosis on human tau in a novel human tau knock-in (htau-KI) mouse model could help to reveal new details on their interplay. Methods We studied the effects of a novel human htau-KI under fast-progressing amyloidosis in 5xFAD mice in terms of correlation of gene expression data with human brain regions, development of Alzheimer’s-like pathology, synaptic transmission, and behavior. Results The main findings are an interaction of human beta-amyloid and human tau in crossbred 5xFADxhtau-KI observed at transcriptional level and corroborated by electrophysiology and histopathology. The comparison of gene expression data of the 5xFADxhtau-KI mouse model to 5xFAD, control mice and to human AD patients revealed conspicuous changes in pathways related to mitochondria biology, extracellular matrix, and immune function. These changes were accompanied by plaque-associated MC1-positive pathological tau that required the htau-KI background. LTP deficits were noted in 5xFAD and htau-KI mice in contrast to signs of rescue in 5xFADxhtau-KI mice. Increased frequencies of miniature EPSCs and miniature IPSCs indicated an upregulated presynaptic function in 5xFADxhtau-KI. Conclusion In summary, the multiple interactions observed between knocked-in human tau and the 5xFAD-driven progressing amyloidosis have important implications for future model development in AD.
Obesity is recognized as a significant risk factor for Alzheimer's disease (AD). Studies have supported the notion that obesity accelerates AD-related pathophysiology in mouse models of AD. The majority of studies, to date, have focused on the use of early-onset AD models. Here, we evaluate the impact of genetic risk factors on late-onset AD (LOAD) in mice fed with a high fat/high sugar diet (HFD). We focused on three mouse models created through the IU/JAX/PITT MODEL-AD Center. These included a combined risk model with
