Co-aggregation with Apolipoprotein E modulates the function of Amyloid-ß in Alzheimer's disease.

Which isoforms of apolipoprotein E (apoE) we inherit determine our risk of developing late-onset Alzheimer's Disease (AD), but the mechanism underlying this link is poorly understood. In particular, the relevance of direct interactions between apoE and amyloid-ß (Aß) remains controversial. Here, single-molecule imaging shows that all isoforms of apoE associate with Aß in the early stages of aggregation and then fall away as fibrillation happens. ApoE-Aß co-aggregates account for ~50% of the mass of diffusible Aß aggregates detected in the frontal cortices of homozygotes with the higher-risk APOE4 gene. We show how dynamic interactions between apoE and Aß tune disease-related functions of Aß aggregates throughout the course of aggregation. Our results connect inherited APOE genotype with the risk of developing AD by demonstrating how, in an isoform- and lipidation-specific way, apoE modulates the aggregation, clearance and toxicity of Aß. Selectively removing non-lipidated apoE4-Aß co-aggregates enhances clearance of toxic Aß by glial cells, and reduces secretion of inflammatory markers and membrane damage, demonstrating a clear path to AD therapeutics.

Bayesian genome-wide TWAS with reference transcriptomic data of brain and blood tissues identified 141 risk genes for Alzheimer's disease dementia.

BACKGROUND: Transcriptome-wide association study (TWAS) is an influential tool for identifying genes associated with complex diseases whose genetic effects are likely mediated through transcriptome. TWAS utilizes reference genetic and transcriptomic data to estimate effect sizes of genetic variants on gene expression (i.e., effect sizes of a broad sense of expression quantitative trait loci, eQTL). These estimated effect sizes are employed as variant weights in gene-based association tests, facilitating the mapping of risk genes with genome-wide association study (GWAS) data. However, most existing TWAS of Alzheimer's disease (AD) dementia are limited to studying only cis-eQTL proximal to the test gene. To overcome this limitation, we applied the Bayesian Genome-wide TWAS (BGW-TWAS) method to leveraging both cis- and trans- eQTL of brain and blood tissues, in order to enhance mapping risk genes for AD dementia. METHODS: We first applied BGW-TWAS to the Genotype-Tissue Expression (GTEx) V8 dataset to estimate cis- and trans- eQTL effect sizes of the prefrontal cortex, cortex, and whole blood tissues. Estimated eQTL effect sizes were integrated with the summary data of the most recent GWAS of AD dementia to obtain BGW-TWAS (i.e., gene-based association test) p-values of AD dementia per gene per tissue type. Then we used the aggregated Cauchy association test to combine TWAS p-values across three tissues to obtain omnibus TWAS p-values per gene. RESULTS: We identified 85 significant genes in prefrontal cortex, 82 in cortex, and 76 in whole blood that were significantly associated with AD dementia. By combining BGW-TWAS p-values across these three tissues, we obtained 141 significant risk genes including 34 genes primarily due to trans-eQTL and 35 mapped risk genes in GWAS Catalog. With these 141 significant risk genes, we detected functional clusters comprised of both known mapped GWAS risk genes of AD in GWAS Catalog and our identified TWAS risk genes by protein-protein interaction network analysis, as well as several enriched phenotypes related to AD. CONCLUSION: We applied BGW-TWAS and aggregated Cauchy test methods to integrate both cis- and trans- eQTL data of brain and blood tissues with GWAS summary data, identifying 141 TWAS risk genes of AD dementia. These identified risk genes provide novel insights into the underlying biological mechanisms of AD dementia and potential gene targets for therapeutics development.

Single-nucleus analysis reveals microenvironment-specific neuron and glial cell enrichment in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a complicated neurodegenerative disease. Neuron-glial cell interactions are an important but not fully understood process in the progression of AD. We used bioinformatic methods to analyze single-nucleus RNA sequencing (snRNA-seq) data to investigate the cellular and molecular biological processes of AD. METHOD: snRNA-seq data were downloaded from Gene Expression Omnibus (GEO) datasets and reprocessed to identify 240,804 single nuclei from healthy controls and patients with AD. The cellular composition of AD was further explored using Uniform Manifold Approximation and Projection (UMAP). Enrichment analysis for the functions of the DEGs was conducted and cell development trajectory analyses were used to reveal underlying cell fate decisions. iTALK was performed to identify ligand-receptor pairs among various cell types in the pathological ecological microenvironment of AD. RESULTS: Six cell types and multiple subclusters were identified based on the snRNA-seq data. A subcluster of neuron and glial cells co-expressing lncRNA-SNHG14, myocardin-related transcription factor A (MRTFA), and MRTFB was found to be more abundant in the AD group. This subcluster was enriched in mitogen-activated protein kinase (MAPK)-, immune-, and apoptosis-related pathways. Through molecular docking, we found that lncRNA-SNHG14 may bind MRTFA and MRTFB, resulting in an interaction between neurons and glial cells. CONCLUSIONS: The findings of this study describe a regulatory relationship between lncRNA-SNHG14, MRTFA, and MRTFB in the six main cell types of AD. This relationship may contribute to microenvironment remodeling in AD and provide a theoretical basis for a more in-depth analysis of AD.

Learning semi-supervised enrichment of longitudinal imaging-genetic data for improved prediction of cognitive decline.

BACKGROUND: Alzheimer's Disease (AD) is a progressive memory disorder that causes irreversible cognitive decline. Given that there is currently no cure, it is critical to detect AD in its early stage during the disease progression. Recently, many statistical learning methods have been presented to identify cognitive decline with temporal data, but few of these methods integrate heterogeneous phenotype and genetic information together to improve the accuracy of prediction. In addition, many of these models are often unable to handle incomplete temporal data; this often manifests itself in the removal of records to ensure consistency in the number of records across participants. RESULTS: To address these issues, in this work we propose a novel approach to integrate the genetic data and the longitudinal phenotype data to learn a fixed-length "enriched" biomarker representation derived from the temporal heterogeneous neuroimaging records. Armed with this enriched representation, as a fixed-length vector per participant, conventional machine learning models can be used to predict clinical outcomes associated with AD. CONCLUSION: The proposed method shows improved prediction performance when applied to data derived from Alzheimer's Disease Neruoimaging Initiative cohort. In addition, our approach can be easily interpreted to allow for the identification and validation of biomarkers associated with cognitive decline.

Apolipoprotein E2 Expression Alters Endosomal Pathways in a Mouse Model With Increased Brain Exosome Levels During Aging.

The polymorphic APOE gene is the greatest genetic determinant of sporadic Alzheimer's disease risk: the APOE4 allele increases risk, while the APOE2 allele is neuroprotective compared with the risk-neutral APOE3 allele. The neuronal endosomal system is inherently vulnerable during aging, and APOE4 exacerbates this vulnerability by driving an enlargement of early endosomes and reducing exosome release in the brain of humans and mice. We hypothesized that the protective effects of APOE2 are, in part, mediated through the endosomal pathway. Messenger RNA analyses showed that APOE2 leads to an enrichment of endosomal pathways in the brain when compared with both APOE3 and APOE4. Moreover, we show age-dependent alterations in the recruitment of key endosomal regulatory proteins to vesicle compartments when comparing APOE2 to APOE3. In contrast to the early endosome enlargement previously shown in Alzheimer's disease and APOE4 models, we detected similar morphology and abundance of early endosomes and retromer-associated vesicles within cortical neurons of aged APOE2 targeted-replacement mice compared with APOE3. Additionally, we observed increased brain extracellular levels of endosome-derived exosomes in APOE2 compared with APOE3 mice during aging, consistent with enhanced endosomal cargo clearance by exosomes to the extracellular space. Our findings thus demonstrate that APOE2 enhances an endosomal clearance pathway, which has been shown to be impaired by APOE4 and which may be protective due to APOE2 expression during brain aging.

Unravelling the complex interplay of cuproptosis, lncRNAs, and immune infiltration in Alzheimer's disease: a step towards novel therapeutic targets.

BACKGROUND: Cuproptosis, a type of cell death involving copper ion accumulation and oxidative stress, has been implicated in the development of Alzheimer's disease (AD). AIM: This study aimed to explore the potential mechanisms and roles of cuproptosis-related genes (CRGs), long non-coding RNAs (lncRNAs), and immune cells in the development of cuproptosis in AD. SUBJECTS AND METHODS: Gene expression profiles of AD were acquired from the Gene Expression Omnibus (GEO) database, and differential analysis was conducted to identify CRGs. Random Forest (RF) modelling was employed to select the most crucial CRGs, which were subsequently validated in the test set. A nomogram model was created to predict AD risk and categorise AD subtypes based on the identified CRGs. A lncRNA-related ceRNA network was built, and immune cell infiltration analysis was conducted. RESULTS: Twelve differentially expressed CRGs were identified in the AD dataset. The RF model pinpointed the five most critical CRGs, which were validated in the test set with an AUC of 0.90. A lncRNA-related ceRNA network was developed, and immune cell infiltration analysis revealed high levels of M1 macrophages and mast cells, along with low levels of memory B cells in AD samples. Correlation analysis unveiled associations between CRGs, lncRNAs, and differentially infiltrating immune cells. CONCLUSION: This research offers insights into the potential mechanisms and roles of CRGs, lncRNAs, and immune cells in the development of cuproptosis in AD. The identified CRGs and lncRNAs may serve as potential therapeutic targets for AD, and the nomogram model may assist in early AD diagnosis and subtyping.

Transcriptomic Analysis of Lipid Metabolism Genes in Alzheimer's Disease: Highlighting Pathological Outcomes and Compartmentalized Immune Status.

The dysregulation of lipid metabolism has been strongly associated with Alzheimer's disease (AD) and has intricate connections with various aspects of disease progression, such as amyloidogenesis, bioenergetic deficit, oxidative stress, neuroinflammation, and myelin degeneration. Here, a comprehensive bioinformatic assessment was conducted on lipid metabolism genes in the brains and peripheral blood of AD-derived transcriptome datasets, characterizing the correlation between differentially expressed genes (DEGs) of lipid metabolism and disease pathologies, as well as immune cell preferences. Through the application of weighted gene co-expression network analysis (WGCNA), modules eigengenes related to lipid metabolism were pinpointed, and the examination of their molecular functions within biological processes, molecular pathways, and their associations with pathological phenotypes and molecular networks has been characterized. Analysis of biological networks indicates notable discrepancies in the expression patterns of the DEGs between neuronal and immune cells, as well as variations in cell type enrichments within both brain tissue and peripheral blood. Additionally, drugs targeting the DEGs from central and peripheral and a diagnostic model for hub genes from the blood were retrieved and assessed, some of which were shown to be useful for therapeutic and diagnostic. These results revealed the distinctive pattern of transcriptionally abnormal lipid metabolism in central, peripheral, and immune cell activation, providing valuable insight into lipid metabolism for diagnosing and guiding more effective treatment for AD.

Electropositive Citric Acid-Polyethyleneimine Carbon Dots Carrying the PINK1 Gene Regulate ATP-Related Metabolic Dysfunction in APP/PS1-N2a Cells.

(1) Background: Alzheimer's disease (AD) is characterized by ß-amyloid (Aß) peptide accumulation and mitochondrial dysfunction during the early stage of disease. PINK1 regulates the balance between mitochondrial homeostasis and bioenergy supply and demand via the PINK1/Parkin pathway, Na+/Ca2+ exchange, and other pathways. (2) Methods: In this study, we synthesized positively charged carbon dots (CA-PEI CDs) using citric acid (CA) and polyethyleneimine (PEI) and used them as vectors to express PINK1 genes in the APP/PS1-N2a cell line to determine mitochondrial function, electron transport chain (ETC) activity, and ATP-related metabolomics. (3) Results: Our findings showed that the CA-PEI CDs exhibit the characteristics of photoluminescence, low toxicity, and concentrated DNA. They are ideal biological carriers for gene delivery. PINK1 overexpression significantly increased the mitochondrial membrane potential in APP/PS1-N2a cells and reduced reactive-oxygen-species generation and Aß1-40 and Aß1-42 levels. An increase in the activity of NADH ubiquinone oxidoreductase (complex I, CI) and cytochrome C oxidase (complex IV, CIV) induces the oxidative phosphorylation of mitochondria, increasing ATP generation. (4) Conclusions: These findings indicate that the PINK gene can alleviate AD by increasing bioenergetic metabolism, reducing Aß1-40 and Aß1-42, and increasing ATP production.

Effects of SPI1-mediated transcriptome remodeling on Alzheimer's disease-related phenotypes in mouse models of Aß amyloidosis.

SPI1 was recently reported as a genetic risk factor for Alzheimer's disease (AD) in large-scale genome-wide association studies. However, it is unknown whether SPI1 should be downregulated or increased to have therapeutic benefits. To investigate the effect of modulating SPI1 levels on AD pathogenesis, we performed extensive biochemical, histological, and transcriptomic analyses using both Spi1-knockdown and Spi1-overexpression mouse models. Here, we show that the knockdown of Spi1 expression significantly exacerbates insoluble amyloid-ß (Aß) levels, amyloid plaque deposition, and gliosis. Conversely, overexpression of Spi1 significantly ameliorates these phenotypes and dystrophic neurites. Further mechanistic studies using targeted and single-cell transcriptomics approaches demonstrate that altered Spi1 expression modulates several pathways, such as immune response pathways and complement system. Our data suggest that transcriptional reprogramming by targeting transcription factors, like Spi1, might hold promise as a therapeutic strategy. This approach could potentially expand the current landscape of druggable targets for AD.

Alzheimer's diseases in America, Europe, and Asian regions: a global genetic variation.

Background: Alzheimer's disease (AD) is one of the multifaceted neurodegenerative diseases influenced by many genetic and epigenetic factors. Genetic factors are merely not responsible for developing AD in the whole population. The studies of genetic variants can provide significant insights into the molecular basis of Alzheimer's disease. Our research aimed to show how genetic variants interact with environmental influences in different parts of the world. Methodology: We searched PubMed and Google Scholar for articles exploring the relationship between genetic variations and global regions such as America, Europe, and Asia. We aimed to identify common genetic variations susceptible to AD and have no significant heterogeneity. To achieve this, we analyzed 35 single-nucleotide polymorphisms (SNPs) from 17 genes (ABCA7, APOE, BIN1, CD2AP, CD33, CLU, CR1, EPHA1, TOMM40, MS4A6A, ARID5B, SORL1, APOC1, MTHFD1L, BDNF, TFAM, and PICALM) from different regions based on previous genomic studies of AD. It has been reported that rs3865444, CD33, is the most common polymorphism in the American and European populations. From TOMM40 and APOE rs2075650, rs429358, and rs6656401, CR1 is the common investigational polymorphism in the Asian population. Conclusion: The results of all the research conducted on AD have consistently shown a correlation between genetic variations and the incidence of AD in the populations of each region. This review is expected to be of immense value in future genetic research and precision medicine on AD, as it provides a comprehensive understanding of the genetic factors contributing to the development of this debilitating disease.

Basal forebrain volume and metabolism in carriers of the Colombian mutation for autosomal dominant Alzheimer's disease.

We aimed to study atrophy and glucose metabolism of the cholinergic basal forebrain in non-demented mutation carriers for autosomal dominant Alzheimer's disease (ADAD). We determined the level of evidence for or against atrophy and impaired metabolism of the basal forebrain in 167 non-demented carriers of the Colombian PSEN1 E280A mutation and 75 age- and sex-matched non-mutation carriers of the same kindred using a Bayesian analysis framework. We analyzed baseline MRI, amyloid PET, and FDG-PET scans of the Alzheimer's Prevention Initiative ADAD Colombia Trial. We found moderate evidence against an association of carrier status with basal forebrain volume (Bayes factor (BF10) = 0.182). We found moderate evidence against a difference of basal forebrain metabolism (BF10 = 0.167). There was only inconclusive evidence for an association between basal forebrain volume and delayed memory and attention (BF10 = 0.884 and 0.184, respectively), and between basal forebrain volume and global amyloid load (BF10 = 2.1). Our results distinguish PSEN1 E280A mutation carriers from sporadic AD cases in which cholinergic involvement of the basal forebrain is already detectable in the preclinical and prodromal stages. This indicates an important difference between ADAD and sporadic AD in terms of pathogenesis and potential treatment targets.

Variants in the MS4A cluster interact with soluble TREM2 expression on biomarkers of neuropathology.

Recent evidence suggests that Alzheimer's disease (AD) genetic risk variants (rs1582763 and rs6591561) of the MS4A locus are genome-wide significant regulators of soluble TREM2 levels such that the minor allele of the protective variant (rs1582763) is associated with higher sTREM2 and lower AD risk while the minor allele of (rs6591561) relates to lower sTREM2 and higher AD risk. Our group previously found that higher sTREM2 relates to higher Aß40, worse blood-brain barrier (BBB) integrity (measured with the CSF/plasma albumin ratio), and higher CSF tau, suggesting strong associations with amyloid abundance and both BBB and neurodegeneration complicate interpretation. We expand on this work by leveraging these common variants as genetic tools to tune the interpretation of high CSF sTREM2, and by exploring the potential modifying role of these variants on the well-established associations between CSF sTREM2 as well as TREM2 transcript levels in the brain with AD neuropathology. Biomarker analyses leveraged data from the Vanderbilt Memory & Aging Project (n = 127, age = 72 ± 6.43) and were replicated in the Alzheimer's Disease Neuroimaging Initiative (n = 399, age = 73 ± 7.39). Autopsy analyses were performed leveraging data from the Religious Orders Study and Rush Memory and Aging Project (n = 577, age = 89 ± 6.46). We found that the protective variant rs1582763 attenuated the association between CSF sTREM2 and Aß40 (ß = -0.44, p-value = 0.017) and replicated this interaction in ADNI (ß = -0.27, p = 0.017). We did not observe this same interaction effect between TREM2 mRNA levels and Aß peptides in brain (Aß total ß = -0.14, p = 0.629; Aß1-38, ß = 0.11, p = 0.200). In contrast to the effects on Aß, the minor allele of this same variant seemed to enhance the association with blood-brain barrier dysfunction (ß = 7.0e-4, p = 0.009), suggesting that elevated sTREM2 may carry a much different interpretation in carriers vs. non-carriers of this allele. When evaluating the risk variant (rs6591561) across datasets, we did not observe a statistically significant interaction against any outcome in VMAP and observed opposing directions of associations in ADNI and ROS/MAP on Aß levels. Together, our results suggest that the protective effect of rs1582763 may act by decoupling the associations between sTREM2 and amyloid abundance, providing important mechanistic insight into sTREM2 changes and highlighting the need to incorporate genetic context into the analysis of sTREM2 levels, particularly if leveraged as a clinical biomarker of disease in the future.

Appendicular lean mass and the risk of stroke and Alzheimer's disease: a mendelian randomization study.

BACKGROUND: Appendicular lean mass (ALM) is a good predictive biomarker for sarcopenia. And previous studies have reported the association between ALM and stroke or Alzheimer's disease (AD), however, the causal relationship is still unclear, The purpose of this study was to evaluate whether genetically predicted ALM is causally associated with the risk of stroke and AD by performing Mendelian randomization (MR) analyses. METHODS: A two-sample MR study was designed. Genetic variants associated with the ALM were obtained from a large genome-wide association study (GWAS) and utilized as instrumental variables (IVs). Summary-level data for stroke and AD were generated from the corresponding GWASs. We used random-effect inverse-variance weighted (IVW) as the main method for estimating causal effects, complemented by several sensitivity analyses, including the weighted median, MR-Egger, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods. Multivariable analysis was further conducted to adjust for confounding factors, including body mass index (BMI), type 2 diabetes mellitus (T2DM), low density lipoprotein-C (LDL-C), and atrial fibrillation (AF). RESULTS: The present MR study indicated significant inverse associations of genetically predicted ALM with any ischemic stroke ([AIS], odds ratio [OR], 0.93; 95% confidence interval [CI], 0.89-0.97; P = 0.002) and AD (OR, 090; 95% CI 0.85-0.96; P = 0.001). Regarding the subtypes of AIS, genetically predicted ALM was related to the risk of large artery stroke ([LAS], OR, 0.86; 95% CI 0.77-0.95; P = 0.005) and small vessel stroke ([SVS], OR, 0.80; 95% CI 0.73-0.89; P < 0.001). Regarding multivariable MR analysis, ALM retained the stable effect on AIS when adjusting for BMI, LDL-C, and AF, while a suggestive association was observed after adjusting for T2DM. And the estimated effect of ALM on LAS was significant after adjustment for BMI and AF, while a suggestive association was found after adjusting for T2DM and LDL-C. Besides, the estimated effects of ALM were still significant on SVS and AD after adjustment for BMI, T2DM, LDL-C, and AF. CONCLUSIONS: The two-sample MR analysis indicated that genetically predicted ALM was negatively related to AIS and AD. And the subgroup analysis of AIS revealed a negative causal effect of genetically predicted ALM on LAS or SVS. Future studies are required to further investigate the underlying mechanisms.

Detecting the effect of genetic diversity on brain composition in an Alzheimer's disease mouse model.

Alzheimer's disease (AD) is broadly characterized by neurodegeneration, pathology accumulation, and cognitive decline. There is considerable variation in the progression of clinical symptoms and pathology in humans, highlighting the importance of genetic diversity in the study of AD. To address this, we analyze cell composition and amyloid-beta deposition of 6- and 14-month-old AD-BXD mouse brains. We utilize the analytical QUINT workflow- a suite of software designed to support atlas-based quantification, which we expand to deliver a highly effective method for registering and quantifying cell and pathology changes in diverse disease models. In applying the expanded QUINT workflow, we quantify near-global age-related increases in microglia, astrocytes, and amyloid-beta, and we identify strain-specific regional variation in neuron load. To understand how individual differences in cell composition affect the interpretation of bulk gene expression in AD, we combine hippocampal immunohistochemistry analyses with bulk RNA-sequencing data. This approach allows us to categorize genes whose expression changes in response to AD in a cell and/or pathology load-dependent manner. Ultimately, our study demonstrates the use of the QUINT workflow to standardize the quantification of immunohistochemistry data in diverse mice, - providing valuable insights into regional variation in cellular load and amyloid deposition in the AD-BXD model.

Estradiol improves behavior in FAD transgenic mice that express APOE3 but not APOE4 after ovariectomy.

Increasing evidence suggests that female individuals have a higher Alzheimer's disease (AD) risk associated with post-menopausal loss of circulating estradiol (E2). However, clinical data are conflicting on whether E2 lowers AD risk. One potential contributing factor is APOE. The greatest genetic risk factor for AD is APOE4, a factor that is pronounced in female individuals post-menopause. Clinical data suggests that APOE impacts the response of AD patients to E2 replacement therapy. However, whether APOE4 prevents, is neutral, or promotes any positive effects of E2 is unclear. Therefore, our goal was to determine whether APOE modulates the impact of E2 on behavior and AD pathology in vivo. To that end, mice that express human APOE3 (E3FAD) or APOE4 (E4FAD) and overproduce Aß42 were ovariectomized at either 4 months (early) or 8 months (late) and treated with vehicle or E2 for 4 months. In E3FAD mice, we found that E2 mitigated the detrimental effect of ovariectomy on memory, with no effect on Aß in the early paradigm and only improved learning in the late paradigm. Although E2 lowered Aß in E4FAD mice in the early paradigm, there was no impact on learning or memory, possibly due to higher Aß pathology compared to E3FAD mice. In the late paradigm, there was no effect on learning/memory and Aß pathology in E4FAD mice. Collectively, these data support the idea that, in the presence of Aß pathology, APOE impacts the response to E2 supplementation post-menopause.

Histone deacetylase-3 regulates the expression of the amyloid precursor protein and its inhibition promotes neuroregenerative pathways in Alzheimer's disease models.

HDAC3 inhibition has been shown to improve memory and reduce amyloid-ß (Aß) in Alzheimer's disease (AD) models, but the underlying mechanisms are unclear. We investigated the molecular effects of HDAC3 inhibition on AD pathology, using in vitro and ex vivo models of AD, based on our finding that HDAC3 expression is increased in AD brains. For this purpose, N2a mouse neuroblastoma cells as well as organotypic brain cultures (OBCSs) of 5XFAD and wild-type mice were incubated with various concentrations of the HDAC3 selective inhibitor RGFP966 (0.1-10 µM) for 24 h. Treatment with RGFP966 or HDAC3 knockdown in N2a cells was associated with an increase on amyloid precursor protein (APP) and mRNA expressions, without alterations in Aß42 secretion. In vitro chromatin immunoprecipitation analysis revealed enriched HDAC3 binding at APP promoter regions. The increase in APP expression was also detected in OBCSs from 5XFAD mice incubated with 1 µM RGFP966, without changes in Aß. In addition, HDAC3 inhibition resulted in a reduction of activated Iba-1-positive microglia and astrocytes in 5XFAD slices, which was not observed in OBCSs from wild-type mice. mRNA sequencing analysis revealed that HDAC3 inhibition modulated neuronal regenerative pathways related to neurogenesis, differentiation, axonogenesis, and dendritic spine density in OBCSs. Our findings highlight the complexity and diversity of the effects of HDAC3 inhibition on AD models and suggest that HDAC3 may have multiple roles in the regulation of APP expression and processing, as well as in the modulation of neuroinflammatory and neuroprotective genes.

MVMRmode: Introducing an R package for plurality valid estimators for multivariable Mendelian randomisation.

BACKGROUND: Mendelian randomisation (MR) is the use of genetic variants as instrumental variables. Mode-based estimators (MBE) are one of the most popular types of estimators used in univariable-MR studies and is often used as a sensitivity analysis for pleiotropy. However, because there are no plurality valid regression estimators, modal estimators for multivariable-MR have been under-explored. METHODS: We use the residual framework for multivariable-MR to introduce two multivariable modal estimators: multivariable-MBE, which uses IVW to create residuals fed into a traditional plurality valid estimator, and an estimator which instead has the residuals fed into the contamination mixture method (CM), multivariable-CM. We then use Monte-Carlo simulations to explore the performance of these estimators when compared to existing ones and re-analyse the data used by Grant and Burgess (2021) looking at the causal effect of intelligence, education, and household income on Alzheimer's disease as an applied example. RESULTS: In our simulation, we found that multivariable-MBE was generally too variable to be much use. Multivariable-CM produced more precise estimates on the other hand. Multivariable-CM performed better than MR-Egger in almost all settings, and Weighted Median under balanced pleiotropy. However, it underperformed Weighted Median when there was a moderate amount of directional pleiotropy. Our re-analysis supported the conclusion of Grant and Burgess (2021), that intelligence had a protective effect on Alzheimer's disease, while education, and household income do not have a causal effect. CONCLUSIONS: Here we introduced two, non-regression-based, plurality valid estimators for multivariable MR. Of these, "multivariable-CM" which uses IVW to create residuals fed into a contamination-mixture model, performed the best. This estimator uses a plurality of variants valid assumption, and appears to provide precise and unbiased estimates in the presence of balanced pleiotropy and small amounts of directional pleiotropy.

Reduction of spermine synthase enhances autophagy to suppress Tau accumulation.

Precise polyamine metabolism regulation is vital for cells and organisms. Mutations in spermine synthase (SMS) cause Snyder-Robinson intellectual disability syndrome (SRS), characterized by significant spermidine accumulation and autophagy blockage in the nervous system. Emerging evidence connects polyamine metabolism with other autophagy-related diseases, such as Tauopathy, however, the functional intersection between polyamine metabolism and autophagy in the context of these diseases remains unclear. Here, we altered SMS expression level to investigate the regulation of autophagy by modulated polyamine metabolism in Tauopathy in Drosophila and human cellular models. Interestingly, while complete loss of Drosophila spermine synthase (dSms) impairs lysosomal function and blocks autophagic flux recapitulating SRS disease phenotype, partial loss of dSms enhanced autophagic flux, reduced Tau protein accumulation, and led to extended lifespan and improved climbing performance in Tauopathy flies. Measurement of polyamine levels detected a mild elevation of spermidine in flies with partial loss of dSms. Similarly, in human neuronal or glial cells, partial loss of SMS by siRNA-mediated knockdown upregulated autophagic flux and reduced Tau protein accumulation. Importantly, proteomics analysis of postmortem brain tissue from Alzheimer's disease (AD) patients showed a significant albeit modest elevation of SMS level. Taken together, our study uncovers a functional correlation between polyamine metabolism and autophagy in AD: SMS reduction upregulates autophagy, suppresses Tau accumulation, and ameliorates neurodegeneration and cell death. These findings provide a new potential therapeutic target for AD.

Pirh2 modulates the mitochondrial function and cytochrome c-mediated neuronal death during Alzheimer's disease.

Pirh2 is an E3 ubiquitin ligase known to regulate the DNA damage responses through ubiquitylation of various participating signaling factors. DNA damage is a key pathological contributor to Alzheimer's disease (AD), therefore, the role of Pirh2 was investigated in streptozotocin and oligomer Aß1-42 induced rodent experimental model of AD. Pirh2 protein abundance increased during AD conditions, and transient silencing of Pirh2 inhibited the disease-specific pathological markers like level of p-Tau, ßamyloid, acetylcholinesterase activity, and neuronal death. Biochemically, Pirh2 silencing significantly attenuated the oxidative stress, depleted mitochondrial membrane potential, cytochrome c translocation from mitochondria to cytosol, and depleted mitochondrial complex-I activity, and ATP level. Pirh2 silencing also inhibited the altered level of VDAC1, hsp75, hexokinase1, t-Bid, caspase-9, and altered level of apoptotic proteins (Bcl-2, Bax). MALDI-TOF/TOF, co-immunoprecipitation, and UbcH13-linked ubiquitylation assay confirmed the interaction of Pirh2 with cytochrome c and the role of Pirh2 in ubiquitylation of cytochrome c, along with Pirh2-dependent altered proteasome activity. Additionally, Pirh2 silencing further inhibited the translocation of mitochondrion-specific endonuclease G and apoptosis-inducing factors to the nucleus and DNA damage. In conclusion, findings suggested the significant implication of Pirh2 in disease pathogenesis, particularly through impaired mitochondrial function, including biochemical alterations, translocation of cytochrome c, endonuclease G and apoptosis-inducing factor, DNA damage, and neuronal apoptosis.

Characterizing dysregulations via cell-cell communications in Alzheimer's brains using single-cell transcriptomes.

BACKGROUND: Alzheimer's disease (AD) is a devastating neurodegenerative disorder affecting 44 million people worldwide, leading to cognitive decline, memory loss, and significant impairment in daily functioning. The recent single-cell sequencing technology has revolutionized genetic and genomic resolution by enabling scientists to explore the diversity of gene expression patterns at the finest resolution. Most existing studies have solely focused on molecular perturbations within each cell, but cells live in microenvironments rather than in isolated entities. Here, we leveraged the large-scale and publicly available single-nucleus RNA sequencing in the human prefrontal cortex to investigate cell-to-cell communication in healthy brains and their perturbations in AD. We uniformly processed the snRNA-seq with strict QCs and labeled canonical cell types consistent with the definitions from the BRAIN Initiative Cell Census Network. From ligand and receptor gene expression, we built a high-confidence cell-to-cell communication network to investigate signaling differences between AD and healthy brains. RESULTS: Specifically, we first performed broad communication pattern analyses to highlight that biologically related cell types in normal brains rely on largely overlapping signaling networks and that the AD brain exhibits the irregular inter-mixing of cell types and signaling pathways. Secondly, we performed a more focused cell-type-centric analysis and found that excitatory neurons in AD have significantly increased their communications to inhibitory neurons, while inhibitory neurons and other non-neuronal cells globally decreased theirs to all cells. Then, we delved deeper with a signaling-centric view, showing that canonical signaling pathways CSF, TGFß, and CX3C are significantly dysregulated in their signaling to the cell type microglia/PVM and from endothelial to neuronal cells for the WNT pathway. Finally, after extracting 23 known AD risk genes, our intracellular communication analysis revealed a strong connection of extracellular ligand genes APP, APOE, and PSEN1 to intracellular AD risk genes TREM2, ABCA1, and APP in the communication from astrocytes and microglia to neurons. CONCLUSIONS: In summary, with the novel advances in single-cell sequencing technologies, we show that cellular signaling is regulated in a cell-type-specific manner and that improper regulation of extracellular signaling genes is linked to intracellular risk genes, giving the mechanistic intra- and inter-cellular picture of AD.