https://mouseion.jax.org/cgi/viewcontent.cgi?article=1141&context=stfb2020

Meta-Analysis of the Alzheimer's Disease Human Brain Transcriptome and Functional Dissection in Mouse Models.

Alzheimer’s disease (AD), the most common form of dementia, is recognized as a heterogeneous disease with diverse pathophysiologic mechanisms. In this study, we interrogate the molecular heterogeneity of AD by analyzing 1543 transcriptomes across five brain regions in two AD cohorts using an integrative network approach. We identify three major molecular subtypes of AD corresponding to different combinations of multiple dysregulated pathways, such as susceptibility to tau-mediated neurodegeneration, amyloid-β neuroinflammation, synaptic signaling, immune activity, mitochondria organization, and myelination. Multiscale network analysis reveals subtype-specific drivers such as GABRB2, LRP10, MSN, PLP1, and ATP6V1A. We further demonstrate that variations between existing AD mouse models recapitulate a certain degree of subtype heterogeneity, which may partially explain why a vast majority of drugs that succeeded in specific mouse models do not align with generalized human trials across all AD subtypes. Therefore, subtyping patients with AD is a critical step toward precision medicine for this devastating disease.

https://advances.sciencemag.org/content/advances/7/2/eabb5398.full.pdf

Molecular subtyping of Alzheimer’s disease using RNA sequencing data reveals novel mechanisms and targets

Alzheimers disease (AD) is the main cause of dementia and it is defined by cognitive decline coupled to extracellular deposit of amyloid-beta protein and intracellular hyperphosphorylation of tau protein. Historically, efforts to target such hallmarks have failed in numerous clinical trials. In addition to these hallmark-targeted approaches, several clinical trials focus on other AD pathological processes, such as inflammation, mitochondrial dysfunction, and oxidative stress. Mitochondria and mitochondrial-related mechanisms have become an attractive target for disease-modifying strategies, as mitochondrial dysfunction prior to clinical onset has been widely described in AD patients and AD animal models. Mitochondrial function relies on both the nuclear and mitochondrial genome. Findings from omics technologies have shed light on AD pathophysiology at different levels (e.g., epigenome, transcriptome and proteome). Most of these studies have focused on the nuclear-encoded components. The first part of this review provides an updated overview of the mechanisms that regulate mitochondrial gene expression and function. The second part of this review focuses on evidence of mitochondrial dysfunction in AD. We have focused on published findings and datasets that study AD. We analyzed published data and provide examples for mitochondrial-related pathways. These pathways are strikingly dysregulated in AD neurons and glia in sex-, cell- and disease stage-specific manners. Analysis of mitochondrial omics data highlights the involvement of mitochondria in AD, providing a rationale for further disease modeling and drug targeting. 

Transcriptomic and epigenomic landscapes of Alzheimer's disease evidence mitochondrial-related pathways.

BACKGROUND Alzheimer's disease is characterized by amyloid‐beta (Aβ) plaques and neurofibrillary tangles. The humanized monoclonal antibody solanezumab was designed to increase the clearance from the brain of soluble Aβ, peptides that may lead to toxic effects in the synapses and precede the deposition of fibrillary amyloid. METHODS We conducted a double‐blind, placebo‐controlled, phase 3 trial involving patients with mild dementia due to Alzheimer's disease, defined as a Mini–Mental State Examination (MMSE) score of 20 to 26 (on a scale from 0 to 30, with higher scores indicating better cognition) and with amyloid deposition shown by means of florbetapir positron‐emission tomography or Aβ1‐42 measurements in cerebrospinal fluid. Patients were randomly assigned to receive solanezumab at a dose of 400 mg or placebo intravenously every 4 weeks for 76 weeks. The primary outcome was the change from baseline to week 80 in the score on the 14‐item cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS‐cog14; scores range from 0 to 90, with higher scores indicating greater cognitive impairment). RESULTS A total of 2129 patients were enrolled, of whom 1057 were assigned to receive solanezumab and 1072 to receive placebo. The mean change from baseline in the ADAS‐cog14 score was 6.65 in the solanezumab group and 7.44 in the placebo group, with no significant between‐group difference at week 80 (difference, ‐0.80; 95% confidence interval, ‐1.73 to 0.14; P=0.10). As a result of the failure to reach significance with regard to the primary outcome in the prespecified hierarchical analysis, the secondary outcomes were considered to be descriptive and are reported without significance testing. The change from baseline in the MMSE score was ‐3.17 in the solanezumab group and ‐3.66 in the placebo group. Adverse cerebral edema or effusion lesions that were observed on magnetic resonance imaging after randomization occurred in 1 patient in the solanezumab group and in 2 in the placebo group. CONCLUSIONS Solanezumab at a dose of 400 mg administered every 4 weeks in patients with mild Alzheimer's disease did not significantly affect cognitive decline. (Funded by Eli Lilly; EXPEDITION3 ClinicalTrials.gov number, NCT01900665.)

Trial of Solanezumab for Mild Dementia Due to Alzheimer’s Disease

The mechanism of Alzheimer9s disease (AD) remains elusive, partly due to the incomplete identification of risk genes. We developed an approach to predict AD-associated genes by learning the functional pattern of curated AD-associated genes from brain gene networks. We created a pipeline to evaluate disease-gene association by interrogating heterogeneous biological networks at different molecular levels. Our analysis showed that top-ranked genes were functionally related to AD. We identified gene modules associated with AD pathways, and found that top-ranked genes were correlated with both neuropathological and clinical phenotypes of AD on independent datasets. We also identified potential causal variants for genes such as FYN and PRKAR1A by integrating brain eQTL and ATAC-seq data. Lastly, we created the ALZLINK web interface, enabling users to exploit the functional relevance of predicted genes to AD. The predictions and pipeline could become a valuable resource to advance the identification of therapeutic targets for AD. Keywords: Alzheimer9s disease; disease gene prediction; functional gene networks

/pdf/genome-wide-prediction-and-integrative-functional-18aes7bj8n.pdf

Genome-wide prediction and integrative functional characterization of Alzheimer's disease-associated genes

SUMMARY To study the molecular mechanisms driving the pathogenesis and identify novel therapeutic targets of late onset Alzheimer’s Disease (LOAD), we performed an integrative network analysis of whole-genome DNA and RNA sequencing profiling of four cortical areas, including the parahippocampal gyrus, across 364 donors spanning the full spectrum of LOAD-related cognitive and neuropathological disease severities. Our analyses revealed thousands of molecular changes and uncovered for the first-time multiple neuron specific gene subnetworks most dysregulated in LOAD. ATP6V1A, a critical subunit of vacuolar-type H+-ATPase (v-ATPase), was predicted to be a key regulator of one neuronal subnetwork and its role in disease-related processes was evaluated through CRISPR-based manipulation of human induced pluripotent stem cell derived neurons and RNAi-based knockdown in transgenic Drosophila models. This study advances our understanding of LOAD pathogenesis by providing the global landscape and detailed circuits of complex molecular interactions and regulations in several key brain regions affected by LOAD and the resulting network models provide a blueprint for developing next generation therapeutics against LOAD.

/pdf/molecular-networks-and-key-regulators-of-the-dysregulated-4b66bvim8y.pdf

Molecular Networks and Key Regulators of the Dysregulated Neuronal System in Alzheimer’s Disease

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Molecular Networks and Key Regulators of the Dysregulated Neuronal System in Alzheimer’s Disease