Abstract The apolipoprotein E (APOE) ε4 allele confers the strongest risk for late-onset Alzheimer’s disease (AD) besides age itself, but the mechanism(s) underlying this risk are debated. The critical test of any proposed AD mechanism is whether it leads to effective treatments. We developed a high-throughput assay to identify inhibitors of apoE4-catalyzed polymerization of the amyloid β (Aβ) peptide into neurotoxic fibrils. Screening a human drug library, we identified five non-toxic, blood-brain-barrier-permeable hit compounds that reduced apoE4-promoted Aβ and tau neuropathology in cultured neurons. Two hit compounds, imipramine and olanzapine, but not other (non-hit) antipsychotics or antidepressants, when prescribed to AD patients for their normal clinical indications, led to improvements in cognition and clinical diagnosis. Imipramine and olanzapine have no structural, functional, or clinical similarities other than their ability to inhibit apoE4-catalyzed Aβ polymerization, thus identifying this mechanism as an essential contribution of apoE4 to AD. One Sentence Summary High-throughput drug screens, studies in Alzheimer’s disease cell culture models, and analyses of human clinical data identified inhibitors of the apoE4-Aβ interaction as a novel class of Alzheimer’s disease therapeutics.
Additional file 15. Custom computer code generated for NACC data analysis. Computer code written in SAS and used to perform all statistical analyses of NACC data is provided in a text file. Computer code written in R and used to generate plots of NACC data is provided as an R file.
Additional file 6. Design of experiments (DOE) assay optimization data. Experimental conditions and raw data for (A) Half-fraction factorial experiment, (B) Response surface experiment #1, and (C) Response surface experiment #2. The RunOrder column indicates randomized order in which the different experimental conditions were prepared in the wells of a plate. The CenterPt column indicates whether the experimental condition is a center point (0) or not (1). The PtType column indicates whether the experimental condition is a corner or axial point (-1 or 1), or a center point (0). The Blocks column indicates whether the experimental condition was included in a single plate run on one day (1) or was included in a second plate repeating the entire experiment on a different day (2). The AUC ThT intensity column indicates the integrated area under the curve of ThT fluorescence intensity measured by the plate reader in arbitrary units (a.u.) over the entire experiment duration. The Fold-change ThT intensity column indicates the fold-change in ThT fluorescence intensity from the beginning to the end of the experiment.
In the post-genomic era, there is a dire need for tools to perform metabolic analyses that include the structural, functional, and regulatory analysis of metabolic networks. This need arose because of the lag between the two phases of metabolic engineering, namely, synthesis and analysis. Molecular biological tools for synthesis like recombinant DNA technology and genetic engineering have advanced a lot farther than tools for systemic analysis. Consequently, bioinformatics is poised to play an important role in bridging the gap between the two phases of metabolic engineering, thereby accelerating the improvement of organisms by using predictive simulations that can be done in minutes rather than mutant constructions that require weeks to months.
In addition, metabolism occurs at a rapid speed compared to other cellular activities and has two states, dynamic state and steady state. Dynamic state analysis sheds more light on the mechanisms and regulation of metabolism than its steady state counterpart. Currently, several in silico tools exist for steady-state analysis of metabolism, but tools for dynamic analysis are lacking. This research focused on simulating the dynamic state of metabolism for predictive analysis of the metabolic changes in an organism during metabolic engineering.
The goals of this research were accomplished by developing two software tools. Metabolome Searcher, a web-based high throughput tool, facilitates putative compound identification and metabolic pathway mapping of mass spectrometry data by applying genome-restriction. The second tool, DynaFlux, uses these compound identifications along with time course data obtained from a mass spectrometer in conjunction with the pathways of interest to simulate and estimate dynamic-state metabolic flux, as well as to analyze the network properties. The features available in DynaFlux are: (1) derivation of the metabolic reconstructions from Pathway Tools software for the simulation; (2) automated building of the mathematical model of the metabolic network; (3) estimation of the kinetic parameters, KR, v, Vmaxf, Vmaxr, and Kdy, using hybrid-mutation random-restart hill climbing search; (4) perturbation studies of enzyme activities; (5) enumeration of feasible routes between two metabolites; (6) determination of the minimal enzyme set and dispensable enzyme set; (7) imputation of missing metabolite data; and (8) visualization of the network.
Abstract Background Carrying the ε4 allele of the apolipoprotein E ( APOE ) gene is the strongest risk factor for Alzheimer’s disease (AD) besides age itself. Having one copy of APOE4 triples the risk for AD, whereas being homozygous for APOE4 increases the risk by greater than 12‐fold. As one potential mechanism, apoE, and especially apoE4, acts as a catalyst to accelerate the polymerization rate of amyloid‐β (Aβ) into neurotoxic oligomers and filaments. Thus, inhibiting this catalytic process is a promising therapeutic approach to preventing AD. Repurposing a known drug to inhibit the apoE4‐Aβ interaction would have numerous benefits such as faster, less expensive testing in clinical trials, and a greater chance of making it to market. Method We developed an apoE4‐Aβ fibrillization assay and screened two small molecule drug repurposing libraries containing more than 3,000 compounds with a history of use in human clinical trials. The cytotoxicity and efficacy of hit compounds were evaluated in transgenic mouse and rat primary neurons. We also modeled changes in cognition using MMSE scores and clinical diagnoses of National Alzheimer’s Coordinating Center (NACC) participants using time slopes and Cox proportional hazards, respectively, and adjusted for age and sex. Result Our high‐throughput screen identified 31 hit compounds that inhibited apoE4‐catalyzed Aβ fibrillization in a dose‐dependent manner. Five of those hit compounds were non‐toxic, blood‐brain barrier permeable, and reduced apoE4‐induced Aβ and tau neuropathology in AD cell culture models. One hit compound was the anti‐depressant imipramine, which, when taken by AD patients, was associated with improved cognition ( P =0.0490) and increased incidence of receiving an improved clinical diagnosis ( P <0.0001), compared to all other anti‐depressants. Another hit compound was the anti‐psychotic olanzapine, which, when taken by AD patients who were APOE4 carriers, was associated with improved cognition ( P =0.0235) and improved clinical diagnosis ( P =0.0435), compared to all other anti‐psychotics. Conclusion We identified five novel inhibitors of the apoE4‐Aβ interaction, two of which were associated with clinical improvements when prescribed to AD patients for their normal indications. These findings validate an apoE‐centric approach to developing new AD therapeutics. This set of small molecules may be useful for preventing or reversing AD, particularly in APOE4 carriers.
Tc1 mouse model of Down syndrome (DS) is functionally trisomic for ∼120 human chromosome 21 (HSA21) classical protein-coding genes. Tc1 mice display features relevant to the DS phenotype, including abnormalities in learning and memory and synaptic plasticity. To determine the molecular basis for the phenotypic features, the levels of 90 phosphorylation-specific and phosphorylation-independent proteins were measured by Reverse Phase Protein Arrays in hippocampus and cortex, and 64 in cerebellum, of Tc1 mice and littermate controls. Abnormal levels of proteins involved in MAP kinase, mTOR, GSK3B and neuregulin signaling were identified in trisomic mice. In addition, altered correlations among the levels of N-methyl-D-aspartate (NMDA) receptor subunits and the HSA21 proteins amyloid beta (A4) precursor protein (APP) and TIAM1, and between immediate early gene (IEG) proteins and the HSA21 protein superoxide dismutase-1 (SOD1) were found in the hippocampus of Tc1 mice, suggesting altered stoichiometry among these sets of functionally interacting proteins. Protein abnormalities in Tc1 mice were compared with the results of a similar analysis of Ts65Dn mice, a DS mouse model that is trisomic for orthologs of 50 genes trisomic in the Tc1 plus an additional 38 HSA21 orthologs. While there are similarities, abnormalities unique to the Tc1 include increased levels of the S100B calcium-binding protein, mTOR proteins RAPTOR and P70S6, the AMP-kinase catalytic subunit AMPKA, the IEG proteins FBJ murine osteosarcoma viral oncogene homolog (CFOS) and activity-regulated cytoskeleton-associated protein (ARC), and the neuregulin 1 receptor ERBB4. These data identify novel perturbations, relevant to neurological function and to some seen in Alzheimer's disease, that may occur in the DS brain, potentially contributing to phenotypic features and influencing drug responses.
Reverse Phase Protein Arrays (RPPA) is a high-throughput technology used to profile levels of protein expression. Handling the large datasets generated by RPPA can be facilitated by appropriate software tools. Here, we describe RPPAware, a free and intuitive software suite that was developed specifically for analysis and visualization of RPPA data. RPPAware is a portable tool that requires no installation and was built using Java. Many modules of the tool invoke R to utilize the statistical features. To demonstrate the utility of RPPAware, data generated from screening brain regions of a mouse model of Down syndrome with 62 antibodies were used as a case study. The ease of use and efficiency of RPPAware can accelerate data analysis to facilitate biological discovery. RPPAware 1.0 is freely available under GNU General Public License from the project website at http://downsyndrome.ucdenver.edu/iddrc/rppaware/home.htm along with a full documentation of the tool.
Abstract Background The apolipoprotein E ( APOE ) ε4 allele confers the strongest risk for late-onset Alzheimer’s disease (AD) besides age itself, but the mechanisms underlying this risk are debated. One hypothesis supported by evidence from multiple labs is that apoE4 binds to the amyloid-β (Aβ) peptide and catalyzes its polymerization into neurotoxic oligomers and fibrils. Inhibiting this early step in the amyloid cascade may thereby reduce or prevent neurodegeneration and AD. Methods Using a design of experiments (DOE) approach, we developed a high-throughput assay to identify inhibitors of apoE4-catalyzed polymerization of Aβ into oligomers and fibrils. We used it to screen the NIH Clinical Collection of small molecule drugs tested previously in human clinical trials. We then evaluated the efficacy and cytotoxicity of the hit compounds in primary neuron models of apoE4-induced Aβ and phosphorylated tau aggregation. Finally, we performed retrospective analyses of the National Alzheimer’s Coordinating Center (NACC) clinical dataset, using Cox regression and Cox proportional hazards models to determine if the use of two FDA-approved hit compounds was associated with better cognitive scores (Mini-Mental State Exam), or improved AD clinical diagnosis, when compared with other medications of the same clinical indication. Results Our high-throughput screen identified eight blood-brain barrier (BBB)-permeable hit compounds that reduced apoE4-catalyzed Aβ oligomer and fibril formation in a dose-dependent manner. Five hit compounds were non-toxic toward cultured neurons and also reduced apoE4-promoted Aβ and tau neuropathology in a dose-dependent manner. Three of the five compounds were determined to be specific inhibitors of apoE4, whereas the other two compounds were Aβ or tau aggregation inhibitors. When prescribed to AD patients for their normal clinical indications, two of the apoE4 inhibitors, imipramine and olanzapine, but not other (non-hit) antipsychotic or antidepressant medications, were associated with improvements in cognition and clinical diagnosis, especially among APOE4 carriers. Conclusions The critical test of any proposed AD mechanism is whether it leads to effective treatments. Our high-throughput screen identified two promising FDA-approved drugs, imipramine and olanzapine, which have no structural, functional, or clinical similarities other than their shared ability to inhibit apoE4-catalyzed Aβ polymerization, thus identifying this mechanism as an essential contribution of apoE4 to AD.
Down syndrome (DS) is caused by an extra copy of the long arm of human chromosome 21 (HSA21) and the increased expression, due to dosage, of HSA21 encoded genes. In addition to intellectual disability, all individuals with DS develop the neuropathology of Alzheimer's Disease (AD) by age 30-40. The amyloid precursor protein gene, APP, that is mutated or duplicated in some familial AD (FAD), is encoded by HSA21, over expressed in DS, and a candidate for causing AD in DS. However, only half of those with DS will develop the AD-like dementia by age 50-60, suggesting that additional HSA21 genes may modulate the effects of APP triplication, and/or protect the DS brain from early onset progression to dementia in spite of neuropathology. In sporadic AD and mouse models of FAD, abnormal levels of a diverse set of proteins, including receptors, scaffold proteins, kinases, phosphatases and cytokines, have been documented, but nothing is known about their possible roles in AD in DS. Here, we compare expression of 26 AD-related proteins in hippocampus of four mouse models of DS, the Ts65Dn, Tc1, Dp (10)1Yey and Dp (17)1Yey, that together provided trisomy of partially overlapping subsets of all HSA21 genes or mouse orthologs. In the Dp(10)1Yey, that is trisomic for HSA21 orthologs mapping to mouse chromosome 10, twelve of 26 AD-related proteins were elevated, while in the Tc1, Dp(17)1Yey and the popular Ts65Dn, six, four and two differed from littermate controls. These data suggest that genes mapping to the HSA21 orthologous regions of mouse chromosomes 10 and 17 contribute to protein perturbations in the DS brain, and possibly AD in DS. Considering the different phenotypic features of the four DS mouse models further suggests that some protein abnormalities may be compensatory and protective for brain function and/or that learning and memory deficits may be age-dependent.
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