scholarly journals Genetic perturbations of disease risk genes in mice capture transcriptomic signatures of late-onset Alzheimer’s disease

2019 ◽  
Author(s):  
Ravi S. Pandey ◽  
Leah Graham ◽  
Asli Uyar ◽  
Christoph Preuss ◽  
Gareth R. Howell ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Animal Models ◽  
Mouse Models ◽  
Genetic Risk ◽  
Late Onset ◽  
Model Organisms ◽  
Similar Data ◽  
Risk Genes ◽  
Genetic Perturbations

ABSTRACTBackgroundNew genetic and genomic resources have identified multiple genetic risk factors for late-onset Alzheimer’s disease (LOAD) and characterized this common dementia at the molecular level. Experimental studies in model organisms can validate these associations and elucidate the links between specific genetic factors and transcriptomic signatures. Animal models based on LOAD-associated genes can potentially connect common genetic variation with LOAD transcriptomes, thereby providing novel insights into basic biological mechanisms underlying the disease.MethodsWe performed RNA-Seq on whole brain samples from a panel of six-month-old female mice, each carrying one of the following mutations: homozygous deletions of Apoe and Clu; hemizygous deletions of Bin1 and Cd2ap; and a transgenic APOEε4. Similar data from a transgenic APP/PS1 model was included for comparison to early-onset variant effects. Weighted gene co-expression network analysis (WGCNA) was used to identify modules of correlated genes and each module was tested for differential expression by strain. We then compared mouse modules with human postmortem brain modules from the Accelerating Medicine’s Partnership for AD (AMP-AD) to determine the LOAD-related processes affected by each genetic risk factor.ResultsMouse modules were significantly enriched in multiple AD-related processes, including immune response, inflammation, lipid processing, endocytosis, and synaptic cell function. WGCNA modules were significantly associated with Apoe−/−, APOEε4, Clu−/−, and APP/PS1 mouse models. Apoe−/−, GFAP-driven APOEε4, and APP/PS1 driven modules overlapped with AMP-AD inflammation and microglial modules; Clu−/− driven modules overlapped with synaptic modules; and APP/PS1 modules separately overlapped with lipid-processing and metabolism modules.ConclusionsThis study of genetic mouse models provides a basis to dissect the role of AD risk genes in relevant AD pathologies. We determined that different genetic perturbations affect different molecular mechanisms comprising AD, and mapped specific effects to each risk gene. Our approach provides a platform for further exploration into the causes and progression of AD by assessing animal models at different ages and/or with different combinations of LOAD risk variants.

scholarly journals Genetic perturbations of disease risk genes in mice capture transcriptomic signatures of late-onset Alzheimer’s disease

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Ravi S. Pandey ◽  
Leah Graham ◽  
Asli Uyar ◽  
Christoph Preuss ◽  
Gareth R. Howell ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Animal Models ◽  
Mouse Models ◽  
Genetic Risk ◽  
Late Onset ◽  
Model Organisms ◽  
Similar Data ◽  
Risk Genes ◽  
Genetic Perturbations

Abstract Background New genetic and genomic resources have identified multiple genetic risk factors for late-onset Alzheimer’s disease (LOAD) and characterized this common dementia at the molecular level. Experimental studies in model organisms can validate these associations and elucidate the links between specific genetic factors and transcriptomic signatures. Animal models based on LOAD-associated genes can potentially connect common genetic variation with LOAD transcriptomes, thereby providing novel insights into basic biological mechanisms underlying the disease. Methods We performed RNA-Seq on whole brain samples from a panel of six-month-old female mice, each carrying one of the following mutations: homozygous deletions of Apoe and Clu; hemizygous deletions of Bin1 and Cd2ap; and a transgenic APOEε4. Similar data from a transgenic APP/PS1 model was included for comparison to early-onset variant effects. Weighted gene co-expression network analysis (WGCNA) was used to identify modules of correlated genes and each module was tested for differential expression by strain. We then compared mouse modules with human postmortem brain modules from the Accelerating Medicine’s Partnership for AD (AMP-AD) to determine the LOAD-related processes affected by each genetic risk factor. Results Mouse modules were significantly enriched in multiple AD-related processes, including immune response, inflammation, lipid processing, endocytosis, and synaptic cell function. WGCNA modules were significantly associated with Apoe−/−, APOEε4, Clu−/−, and APP/PS1 mouse models. Apoe−/−, GFAP-driven APOEε4, and APP/PS1 driven modules overlapped with AMP-AD inflammation and microglial modules; Clu−/− driven modules overlapped with synaptic modules; and APP/PS1 modules separately overlapped with lipid-processing and metabolism modules. Conclusions This study of genetic mouse models provides a basis to dissect the role of AD risk genes in relevant AD pathologies. We determined that different genetic perturbations affect different molecular mechanisms comprising AD, and mapped specific effects to each risk gene. Our approach provides a platform for further exploration into the causes and progression of AD by assessing animal models at different ages and/or with different combinations of LOAD risk variants.

scholarly journals A novel systems biology approach to evaluate mouse models of late-onset Alzheimer’s disease

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Christoph Preuss ◽  
◽  
Ravi Pandey ◽  
Erin Piazza ◽  
Alexander Fine ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Animal Models ◽  
Mouse Models ◽  
Late Onset ◽  
Cost Effective ◽  
Common Disease ◽  
Disease Genes ◽  
Postmortem Human Brain ◽  
5Xfad Mouse

Abstract Background Late-onset Alzheimer’s disease (LOAD) is the most common form of dementia worldwide. To date, animal models of Alzheimer’s have focused on rare familial mutations, due to a lack of frank neuropathology from models based on common disease genes. Recent multi-cohort studies of postmortem human brain transcriptomes have identified a set of 30 gene co-expression modules associated with LOAD, providing a molecular catalog of relevant endophenotypes. Results This resource enables precise gene-based alignment between new animal models and human molecular signatures of disease. Here, we describe a new resource to efficiently screen mouse models for LOAD relevance. A new NanoString nCounter® Mouse AD panel was designed to correlate key human disease processes and pathways with mRNA from mouse brains. Analysis of the 5xFAD mouse, a widely used amyloid pathology model, and three mouse models based on LOAD genetics carrying APOE4 and TREM2*R47H alleles demonstrated overlaps with distinct human AD modules that, in turn, were functionally enriched in key disease-associated pathways. Comprehensive comparison with full transcriptome data from same-sample RNA-Seq showed strong correlation between gene expression changes independent of experimental platform. Conclusions Taken together, we show that the nCounter Mouse AD panel offers a rapid, cost-effective and highly reproducible approach to assess disease relevance of potential LOAD mouse models.

scholarly journals A novel systems biology approach to evaluate mouse models of late-onset Alzheimer’s disease

2019 ◽  
Author(s):  
Christoph Preuss ◽  
Ravi Pandey ◽  
Erin Piazza ◽  
Alexander Fine ◽  
Asli Uyar ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Animal Models ◽  
Mouse Models ◽  
Late Onset ◽  
Cost Effective ◽  
Common Disease ◽  
Disease Genes ◽  
Postmortem Human Brain ◽  
Disease Relevance

ABSTRACTBackgroundLate-onset Alzheimer’s disease (LOAD) is the most common form of dementia worldwide. To date, animal models of Alzheimer’s have focused on rare familial mutations, due to a lack of frank neuropathology from models based on common disease genes. Recent multi-cohort studies of postmortem human brain transcriptomes have identified a set of 30 gene co-expression modules associated with LOAD, providing a molecular catalog of relevant endophenotypes.ResultsThis resource enables precise gene-based alignment between new animal models and human molecular signatures of disease. Here, we describe a new resource to efficiently screen mouse models for LOAD relevance. A new NanoString nCounter® Mouse AD panel was designed to correlate key human disease processes and pathways with mRNA from mouse brains. Analysis of three mouse models based on LOAD genetics, carrying APOE4 and TREM2*R47H alleles, demonstrated overlaps with distinct human AD modules that, in turn, are functionally enriched in key disease-associated pathways. Comprehensive comparison with full transcriptome data from same-sample RNA-Seq shows strong correlation between gene expression changes independent of experimental platform.ConclusionsTaken together, we show that the nCounter Mouse AD panel offers a rapid, cost-effective and highly reproducible approach to assess disease relevance of potential LOAD mouse models.

scholarly journals APOEe4.Trem2*R47H Mice Show Changes in Alzheimer’s Disease-Relevant Processes in the Absence of Amyloid Plaques

2021 ◽  
Author(s):  
Kevin P. Kotredes ◽  
Adrian Oblak ◽  
Ravi S. Pandey ◽  
Peter Bor-Chian Lin ◽  
Dylan Garceau ◽  
...  
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Mouse Models ◽  
Genetic Risk ◽  
Late Onset ◽  
Model Organism ◽  
Amyloid Plaque ◽  
Genetic Risk Factors ◽  
Mouse Strains

Abstract Late-onset Alzheimer’s disease (LOAD) is the most common human neurodegenerative disease. Legacy amyloidogenic mouse models have been useful for understanding disease progression, however in the face of failing human trials more focus on disease translation with new mouse strains that better model human Alzheimer’s disease (AD) is required. MODEL-AD (Model Organism Development and Evaluation for Late-onset AD) groups are identifying and integrating disease-relevant, humanized gene sequences from public databases to create more translatable mouse models for therapy development. Mice expressing strong genetic risk factors for LOAD, APOEe4 and Trem2*R47H, were extensively aged and assayed using a multi-disciplined phenotyping approach associated with and relative to human AD pathology. Behavioral, transcriptomic, metabolic, and neuropathological assays identified sex and age as the main sources of variation between genotypes including age-specific enrichment of AD-related processes in the absence of mouse amyloid plaque formation. These data provide an important, baseline understanding of the individual effects and interaction between two strong genetic risk factors for LOAD. These two alleles together form a sensitized, background strain (B6.APOE4.Trem2*R47H, which we have termed ‘LOAD1’) necessary to examine how important underlying risk factors interact with any subsequent genetic or environmental cues to drive pathology.

scholarly journals Interaction of Alzheimer’s Disease-Associated Genetic Risk with Indicators of Socioeconomic Position on Mild Cognitive Impairment in the Heinz Nixdorf Recall Study

2021 ◽  
pp. 1-11
Author(s):  
Mirjam Frank ◽  
Jonas Hensel ◽  
Lisa Baak ◽  
Sara Schramm ◽  
Nico Dragano ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Socioeconomic Position ◽  
Genetic Risk ◽  
Late Onset ◽  
Heinz Nixdorf Recall Study ◽  
Low Education ◽  
Additive Scale

Background: The apolipoprotein E (APOE) ɛ4 allele is reported to be a strong genetic risk factor for mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Additional genetic loci have been detected that influence the risk for late-onset AD. As socioeconomic position (SEP) is also strongly related to cognitive decline, SEP has been suggested to be a possible modifier of the genetic effect on MCI. Objective: To investigate whether APOE ɛ4 and a genetic sum score of AD-associated risk alleles (GRSAD) interact with SEP indicators to affect MCI in a population-based cohort. Methods: Using data of 3,834 participants of the Heinz Nixdorf Recall Study, APOE ɛ4 and GRSAD by SEP interactions were assessed using logistic regression models, as well as SEP-stratified genetic association analysis. Interaction on additive scale was calculated using the relative excess risk due to interaction (RERI). All analysis were additionally stratified by sex. Results: Indication for interaction on the additive scale was found between APOE ɛ4 and low education on MCI (RERI: 0.52 [95% -confidence interval (CI): 0.01; 1.03]). The strongest genetic effects of the APOE ɛ4 genotype on MCI were observed in groups of low education (Odds ratio (OR): 1.46 [95% -CI: 0.79; 2.63] for≤10 years of education versus OR: 1.00 [95% -CI: 0.43; 2.14] for≥18 years of education). Sex stratified results showed stronger effects in women. No indication for interaction between the GRSAD and SEP indicators on MCI was observed. Conclusion: Results indicate that low education may have an impact on APOE ɛ4 expression on MCI, especially among women.

scholarly journals ApoE4 attenuates cortical neuronal activity and impairs memory in young apoE4 rats

2021 ◽  
Author(s):  
Ilona Har-Paz ◽  
Elor Arieli ◽  
Anan Moran
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Risk Factor ◽  
Neuronal Activity ◽  
Genetic Risk ◽  
Cortical Neurons ◽  
Late Onset ◽  
Genetic Risk Factor ◽  
Normal Brain ◽  
Brain Functions

AbstractThe E4 allele of apolipoprotein E (apoE4) is the strongest genetic risk factor for late-onset Alzheimer’s disease (AD). However, apoE4 may cause innate brain abnormalities before the appearance of AD related neuropathology. Understanding these primary dysfunctions is vital for early detection of AD and the development of therapeutic strategies for it. Recently we have shown impaired extra-hippocampal memory in young apoE4 mice – a deficit that was correlated with attenuated structural pre-synaptic plasticity in cortical and subcortical regions. Here we test the hypothesis that these early structural deficits impact learning via changes in basal and stimuli evoked neuronal activity. We recorded extracellular neuronal activity from the gustatory cortex (GC) of three-month-old humanized apoE4 and wildtype rats, before and after conditioned taste aversion (CTA) training. Despite normal sucrose drinking behavior before CTA, young apoE4 rats showed impaired CTA learning, consistent with our previous results in apoE4 mice. This behavioral deficit was correlated with decreased basal and taste-evoked firing rates in both putative excitatory and inhibitory GC neurons. Single neuron and ensemble analyses of taste coding demonstrated that apoE4 neurons could be used to correctly classify tastes, but were unable to undergo plasticity to support learning. Our results suggest that apoE4 impacts brain excitability and plasticity early in life and may act as an initiator for later AD pathologies.Significant statementThe ApoE4 allele is the strongest genetic risk-factor for late-onset Alzheimer’s disease (AD), yet the link between apoE4 and AD is still unclear. Recent molecular and in-vitro studies suggest that apoE4 interferes with normal brain functions decades before the development of its related AD neuropathology. Here we recorded the activity of cortical neurons from young apoE4 rats during extra-hippocampal learning to study early apoE4 neuronal activity abnormalities, and their effects over coding capacities. We show that apoE4 drastically reduces basal and stimuli-evoked cortical activity in both excitatory and inhibitory neurons. The apoE4-induced activity attenuation did not prevent coding of stimuli identity and valence, but impaired capacity to undergo activity changes to support learning. Our findings support the hypothesis that apoE4 interfere with normal neuronal plasticity early in life; a deficit that may lead to late-onset AD development.

scholarly journals Translating genetic risk variants in disease‐associated enhancers into novel mouse models of Alzheimer’s disease

2020 ◽  
Vol 16 (S2) ◽  
Author(s):  
Christoph Preuss ◽  
Xi Chen ◽  
Kathleen Chen ◽  
Chandra Theesfeld ◽  
Evan Cofer ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Mouse Models ◽  
Genetic Risk ◽  
Risk Variants ◽  
Genetic Risk Variants

P3-006: Late-onset Alzheimer's disease genetic risk factors in two Canadian cohorts: CSHA and ACCORD

2013 ◽  
Vol 9 ◽  
pp. P551-P552
Author(s):  
Ardeshir Omoumi ◽  
Alice Fok ◽  
Talitha Greenwood ◽  
Dessa Sadovnick ◽  
Howard Feldman ◽  
...  
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Risk ◽  
Late Onset ◽  
Genetic Risk Factors

scholarly journals Pyk2 overexpression in postsynaptic neurons blocks amyloid β1–42-induced synaptotoxicity in microfluidic co-cultures

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Devrim Kilinc ◽  
Anaïs-Camille Vreulx ◽  
Tiago Mendes ◽  
Amandine Flaig ◽  
Diego Marques-Coelho ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Amyloid Precursor Protein ◽  
Genetic Risk ◽  
Association Studies ◽  
Amyloid Β ◽  
Precursor Protein ◽  
Genome Wide Association Studies ◽  
Risk Genes ◽  
The Impact

Abstract Recent meta-analyses of genome-wide association studies identified a number of genetic risk factors of Alzheimer’s disease; however, little is known about the mechanisms by which they contribute to the pathological process. As synapse loss is observed at the earliest stage of Alzheimer’s disease, deciphering the impact of Alzheimer’s risk genes on synapse formation and maintenance is of great interest. In this article, we report a microfluidic co-culture device that physically isolates synapses from pre- and postsynaptic neurons and chronically exposes them to toxic amyloid β peptides secreted by model cell lines overexpressing wild-type or mutated (V717I) amyloid precursor protein. Co-culture with cells overexpressing mutated amyloid precursor protein exposed the synapses of primary hippocampal neurons to amyloid β1–42 molecules at nanomolar concentrations and induced a significant decrease in synaptic connectivity, as evidenced by distance-based assignment of postsynaptic puncta to presynaptic puncta. Treating the cells with antibodies that target different forms of amyloid β suggested that low molecular weight oligomers are the likely culprit. As proof of concept, we demonstrate that overexpression of protein tyrosine kinase 2 beta—an Alzheimer’s disease genetic risk factor involved in synaptic plasticity and shown to decrease in Alzheimer’s disease brains at gene expression and protein levels—selectively in postsynaptic neurons is protective against amyloid β1–42-induced synaptotoxicity. In summary, our lab-on-a-chip device provides a physiologically relevant model of Alzheimer’s disease-related synaptotoxicity, optimal for assessing the impact of risk genes in pre- and postsynaptic compartments.

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