Alzheimer's Disease

Oboudiyat, Carly; Glazer, Hilary; Seifan, Alon; Greer, Christine; Isaacson, Richard S.

doi:10.1055/s-0033-1359319

Cited by 123 publications

(99 citation statements)

References 115 publications

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“…The biological coherence of the protein expression, compared to gene expression data, with respect to association with AD clinical features, was noteworthy, suggesting proteomic data may be a more informative measure for identifying important dysregulated pathways. Ab, a hallmark of AD (6), was consistently the protein with the highest expression in cases relative to controls, whereas VGF was the most downregulated. DE proteins are annotated for energy metabolism and immune and nervous system related processes, all previously implicated in AD (8,(94)(95)(96)(97)(98); our co-expression network analyses based in part on these DE protein studies, have further identified novel, potentially druggable targets within these pathways.…”

Section: Discussionmentioning

confidence: 95%

“…The brains of AD patients have hallmark senile plaques in the neuropil and around brain blood vessels, composed of accumulated amyloid beta (Ab), and neurofibrillary tangles (NFT) inside neurons, comprised of microtubule-associated hyperphosphorylated Tau protein (2). While therapeutic strategies to target Ab and tau pathologies have been aggressively pursued over the past two decades, the failure to date to deliver efficacious treatments from these efforts has increased the urgency to identify and pursue different mechanisms underlying AD, such as the immune system, through microglial cells, that has more recently been shown to play a key role in AD (3)(4)(5)(6)(7)(8)(9). Furthermore, with a handful of drugs lessening some of the symptoms of AD, no effective drugs are currently available that prevent, halt or reverse the onset or progression of this disease.…”

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confidence: 99%

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Multiscale causal network models of Alzheimer’s disease identify VGF as a key regulator of disease

Lin²,

Wang

et al. 2018

Preprint

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Though discovered over 100 years ago, the molecular foundation of sporadic Alzheimer's disease (AD) remains elusive. To elucidate its complex nature, we constructed multiscale causal network models on a large human AD multi-omics dataset, integrating clinical features of AD, DNA variation, and gene and protein expression into probabilistic causal models that enabled detection and prioritization of high-confidence key drivers of AD, including the top predicted key driver VGF. Overexpression of neuropeptide precursor VGF in 5xFAD mice partially rescued beta-amyloid-mediated memory impairment and neuropathology. Molecular validation of network predictions downstream of VGF was achieved, with significant enrichment for homologous genes identified as differentially expressed in 5xFAD brains overexpressing VGF versus controls. Our findings support a causal and/or protective role for VGF in AD pathogenesis and progression. One sentence summary: VGF protects against Alzheimer's diseaseAlthough VGF has been reported to regulate fear and spatial memories in mouse models (35,37,38), and to be an AD biomarker, with VGF-derived peptides found to be reduced in the CSF of AD patients compared to healthy controls (39-46), VGF has not previously been causally associated with AD. We determined through our network models that VGF was the only downregulated KD for AD that was conserved across the RNA, protein, and combined RNA and protein networks we constructed. We replicated these findings in other brain regions (47) and in an independent dataset (48,49), and observed evidence of genetic association in the largest AD GWAS to date (10). Given VGF's status as the top KD we identified in our networks, we overexpressed VGF in the 5xFAD mouse model of familial AD and found that it not only lowered overall amyloid plaque and Tau-associated dystrophic neurite levels, but it significantly perturbed gene expression traits that were enriched for genes predicted by our networks to change in response to VGF modulation. Taken together, these results provide molecular and functional validation of our multiscale causal network analysis finding of VGF as a driver of AD pathophysiology. We conclude that the genes and clinical features linked to VGF provide novel insights into the mechanisms underlying AD risk and pathogenesis.Results: Our overall strategy for elucidating the complexity of AD is depicted in Fig. 1 (Fig. S1) and is centered on the objective, data-driven construction of predictive network models of AD that can then be queried to identify network components causally associated with AD. The master regulators that modulate the state of these AD-associated network components can then be readily identified from the network model. We have previously developed and applied the network reconstruction algorithm, RIMBANET, which statistically infers causal relationships between DNA variation, gene expression, protein expression and clinical features that are scored

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Section: Discussionmentioning

confidence: 95%

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confidence: 99%

Multiscale causal network models of Alzheimer’s disease identify VGF as a key regulator of disease

Lin²,

Wang

et al. 2018

Preprint

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“…In particular, among the possible triggers of the neurodegenerative process and in particular of AD, nutrients have the potential to be either prevention-or riskrelated factors. The study of their effects at the gene expression level, by means of nutrigenomic analyses, is a field of broad scientific interest [77,78]. Despite some conflicting evidences, plant-based, plant-rich diets and plant-derived bioactive nutrients appear to inhibit neuroinflammation and neurodegeneration molecular and cellular processes [79] and seem to be particularly beneficial in the management of early stages of cognitive impairment [80][81][82][83][84].…”

Section: The Population and Individual Levels: Epidemiological Studiementioning

confidence: 99%

A Human-Based Integrated Framework forAlzheimer’s Disease Research

Pistollato

Cavanaugh

Chandrasekera

2015

JAD

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Abstract. Animal models of Alzheimer's disease (AD) have been extensively utilized for decades in an effort to elucidate the pathophysiological mechanisms of this disease and to test novel therapeutic approaches. However, research success has not effectively translated into therapeutic success for human patients. This translational failure is partially due to the overuse of animal models that cannot accurately recapitulate human AD etiopathogenesis or drug responses and the inadequate use of human-relevant research methods. Here, we propose how to mitigate this translational barrier by employing human-based methods to elucidate disease processes occurring at multiple levels of complexity, accounting for gene and protein expression and the impact of disease at the cellular, tissue/organ, individual, and population levels. In particular, novel human-based cellular and computational models, together with epidemiological and clinical studies, represent the ideal tools to facilitate human-relevant data acquisition, in the effort to better elucidate AD pathogenesis in a human-based setting and design more effective treatments and preventive strategies. Our analysis indicates that a paradigm shift toward human-based, rather than animal-based research is required in the face of the ever-increasing prevalence of AD in the 21st century.

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“…Dementia is a global health burden . According to a recent report in 2015 from the World Health Organization, there are 47.5 million people living with dementia worldwide, and over 60% of dementia cases are caused by Alzheimer's disease (AD) .…”

mentioning

confidence: 99%

“…D ementia is a global health burden. 1,2 According to a recent report in 2015 from the World Health Organization, there are 47.5 million people living with dementia worldwide, and over 60% of dementia cases are caused by Alzheimer's disease (AD). 3 With a global aging population, the total number of people with AD or dementia is expected to significantly increase over the next 10 years.…”

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confidence: 99%