The effect of Abi3 locus deletion on the progression of Alzheimer's disease-related pathologies

The WAVE complex in developmental and adulthood brain disorders

Actin polymerization and depolymerization are fundamental cellular processes required not only for the embryonic and postnatal development of the brain but also for the maintenance of neuronal plasticity and survival in the adult and aging brain. The orchestrated organization of actin filaments is controlled by various actin regulatory proteins. Wiskott‒Aldrich syndrome protein-family verprolin-homologous protein (WAVE) members are key activators of ARP2/3 complex-mediated actin polymerization. WAVE proteins exist as heteropentameric complexes together with regulatory proteins, including CYFIP, NCKAP, ABI and BRK1. The activity of the WAVE complex is tightly regulated by extracellular cues and intracellular signaling to execute its roles in specific intracellular events in brain cells. Notably, dysregulation of the WAVE complex and WAVE complex-mediated cellular processes confers vulnerability to a variety of brain disorders. De novo mutations in WAVE genes and other components of the WAVE complex have been identified in patients with developmental disorders such as intellectual disability, epileptic seizures, schizophrenia, and/or autism spectrum disorder. In addition, alterations in the WAVE complex are implicated in the pathophysiology of Alzheimer's disease and Parkinson's disease, as well as in behavioral adaptations to psychostimulants or maladaptive feeding.

Deletion of miR-33, a regulator of the ABCA1-APOE pathway, ameliorates neuropathological phenotypes in APP/PS1 mice

INTRODUCTION

Rare variants in ABCA1 increase the risk of developing Alzheimer's disease (AD). ABCA1 facilitates the lipidation of apolipoprotein E (apoE). This study investigated whether microRNA-33 (miR-33)-mediated regulation of this ABCA1-APOE pathway affects phenotypes of an amyloid mouse model.

METHODS

We generated mir-33+/+;APP/PS1 and mir-33-/-;APP/PS1 mice to determine changes in amyloid pathology using biochemical and histological analyses. We used RNA sequencing and mass spectrometry to identify the transcriptomic and proteomic changes between our genotypes. We also performed mechanistic experiments by determining the role of miR-33 in microglial migration and amyloid beta (Aβ) phagocytosis.

RESULTS

Mir-33 deletion increases ABCA1 levels and reduces Aβ accumulation and glial activation. Multi-omics studies suggested miR-33 regulates the activation and migration of microglia. We confirm that the inhibition of miR-33 significantly increases microglial migration and Aβ phagocytosis.

DISCUSSION

These results suggest that miR-33 might be a potential drug target by modulating ABCA1 level, apoE lipidation, Aβ level, and microglial function.

HIGHLIGHTS

Loss of microRNA-33 (miR-33) increased ABCA1 protein levels and the lipidation of apolipoprotein E. Loss of miR-33 reduced amyloid beta (Aβ) levels, plaque deposition, and gliosis. mRNAs and proteins dysregulated by miR-33 loss relate to microglia and Alzheimer's disease. Inhibition of miR-33 increased microglial migration and Aβ phagocytosis in vitro.

Network dynamics-based subtyping of Alzheimer's disease with microglial genetic risk factors

BACKGROUND

The potential of microglia as a target for Alzheimer's disease (AD) treatment is promising, yet the clinical and pathological diversity within microglia, driven by genetic factors, poses a significant challenge. Subtyping AD is imperative to enable precise and effective treatment strategies. However, existing subtyping methods fail to comprehensively address the intricate complexities of AD pathogenesis, particularly concerning genetic risk factors. To address this gap, we have employed systems biology approaches for AD subtyping and identified potential therapeutic targets.

METHODS

We constructed patient-specific microglial molecular regulatory network models by utilizing existing literature and single-cell RNA sequencing data. The combination of large-scale computer simulations and dynamic network analysis enabled us to subtype AD patients according to their distinct molecular regulatory mechanisms. For each identified subtype, we suggested optimal targets for effective AD treatment.

RESULTS

To investigate heterogeneity in AD and identify potential therapeutic targets, we constructed a microglia molecular regulatory network model. The network model incorporated 20 known risk factors and crucial signaling pathways associated with microglial functionality, such as inflammation, anti-inflammation, phagocytosis, and autophagy. Probabilistic simulations with patient-specific genomic data and subsequent dynamics analysis revealed nine distinct AD subtypes characterized by core feedback mechanisms involving SPI1, CASS4, and MEF2C. Moreover, we identified PICALM, MEF2C, and LAT2 as common therapeutic targets among several subtypes. Furthermore, we clarified the reasons for the previous contradictory experimental results that suggested both the activation and inhibition of AKT or INPP5D could activate AD through dynamic analysis. This highlights the multifaceted nature of microglial network regulation.

CONCLUSIONS

These results offer a means to classify AD patients by their genetic risk factors, clarify inconsistent experimental findings, and advance the development of treatments tailored to individual genotypes for AD.

Cell-type specific inference from bulk RNA-sequencing data by integrating single cell reference profiles via EPIC-unmix

Cell type specific (CTS) analysis is essential to reveal biological insights obscured in bulk tissue data. However, single-cell (sc) or single-nuclei (sn) resolution data are still cost-prohibitive for large-scale samples. Thus, computational methods to perform deconvolution from bulk tissue data are highly valuable. We here present EPIC-unmix, a novel two-step empirical Bayesian method integrating reference sc/sn RNA-seq data and bulk RNA-seq data from target samples to enhance the accuracy of CTS inference. We demonstrate through comprehensive simulations across three tissues that EPIC-unmix achieved 4.6% - 109.8% higher accuracy compared to alternative methods. By applying EPIC-unmix to human bulk brain RNA-seq data from the ROSMAP and MSBB cohorts, we identified multiple genes differentially expressed between Alzheimer's disease (AD) cases versus controls in a CTS manner, including 57.4% novel genes not identified using similar sample size sc/snRNA-seq data, indicating the power of our in-silico approach. Among the 6-69% overlapping, 83%-100% are in consistent direction with those from sc/snRNA-seq data, supporting the reliability of our findings. EPIC-unmix inferred CTS expression profiles similarly empowers CTS eQTL analysis. Among the novel eQTLs, we highlight a microglia eQTL for AD risk gene AP3B2, obscured in bulk and missed by sc/snRNA-seq based eQTL analysis. The variant resides in a microglia-specific cCRE, forming chromatin loop with AP3B2 promoter region in microglia. Taken together, we believe EPIC-unmix will be a valuable tool to enable more powerful CTS analysis.

Cognitive impairment in Alzheimer's disease FAD4T mouse model: Synaptic loss facilitated by activated microglia via C1qA

Alzheimer's disease (AD) is a chronic and progressive neurodegenerative disorder characterized by cognitive dysfunction. The connection between neuroinflammation and abnormal synaptic function in AD is recognized, but the underlying mechanisms remain unclear. In this study, we utilized a mouse model of AD, FAD4T mice aged 6-7 months, to investigate the molecular changes affecting cognitive impairment. Behavior tests showed that FAD4T mice exhibited impaired spatial memory compared with their wild-type littermates. Immunofluorescence staining revealed the presence of Aβ plaques and abnormal glial cell activation as well as changes in microglial morphology in the cortex and hippocampus of FAD4T mice. Synaptic function was impaired in FAD4T mice. Patch clamp recordings of hippocampal neurons revealed reduced amplitude of miniature excitatory postsynaptic currents. Additionally, Golgi staining showed decreased dendritic spine density in the cortex and hippocampus of FAD4T mice, indicating aberrant synapse morphology. Moreover, hippocampal PSD-95 and NMDAR1 protein levels decreased in FAD4T mice. RNA-seq analysis revealed elevated expression of immune system and proinflammatory genes, including increased C1qA protein and mRNA levels, as well as higher expression of TNF-α and IL-18. Taken together, our findings suggest that excessive microglia activation mediated by complement factor C1qA may contribute to aberrant synaptic pruning, resulting in synapse loss and disrupted synaptic transmission, ultimately leading to AD pathogenesis and behavioral impairments in the FAD4T mouse model. Our study provides valuable insights into the underlying mechanisms of cognitive impairments and preliminarily explores a potentially effective treatment approach targeting on C1qA for AD.