Single-cell multiregion dissection of Alzheimer's disease

Clinical phenotypes of Alzheimer's disease: investigating atrophy patterns and their pathological correlates

BACKGROUND

In Alzheimer's disease (AD), MRI atrophy patterns can distinguish between amnestic (typical) and non-amnestic (atypical) clinical phenotypes and are increasingly used for diagnosis and outcome measures in clinical trials. However, understanding how protein accumulation and other key features of neurodegeneration influence these imaging measurements, are lacking. The current study aimed to assess regional MRI patterns of cortical atrophy across clinical AD phenotypes, and their association with amyloid-beta (Aβ), phosphorylated tau (pTau), neuro-axonal degeneration and microvascular deterioration.

METHODS

Post-mortem in-situ 3DT1 3 T-MRI data was obtained from 33 AD (17 typical, 16 atypical) and 16 control brain donors. Additionally, ante-mortem 3DT1 3 T-MRI scans of brain donors were collected if available. Regional volumes were obtained from MRI scans using an atlas based parcellation software. Eight cortical brain regions were selected from formalin-fixed right hemispheres of brain donors and then immunostained for Aβ, pTau, neurofilament light, and collagen IV. Group comparisons and volume-pathology associations were analyzed using linear mixed models corrected for age, sex, post-mortem delay, and intracranial volume.

RESULTS

Compared to controls, both typical and atypical AD showed volume loss in the temporo-occipital cortex, while typical AD showed additional volume loss in the parietal cortex. Posterior cingulate volume was lower in typical AD compared to atypical AD (- 6.9%, p = 0.043). In AD, a global positive association between MRI cortical volume and Aβ load (βs = 0.21, p = 0.010), and a global negative association with NfL load (βs = - 0.18, p = 0.018) were observed. Regionally, higher superior parietal gyrus volume was associated with higher Aβ load in typical AD (βs = 0.47, p = 0.004), lower middle frontal gyrus volume associated with higher NfL load in atypical AD (βs = - 0.50, p < 0.001), and lower hippocampal volume associated with higher COLIV load in typical AD (βs = - 1.69, p < 0.001). Comparing post-mortem with ante-mortem scans showed minimal volume differences at scan-intervals within 2 years, highlighting the translational aspect of this study.

CONCLUSION

For both clinical phenotypes, cortical volume is affected by Aβ and neuro-axonal damage, but in opposing directions. Differences in volume-pathology relationships between clinical phenotypes are region-specific. The findings of this study could improve the interpretation of MRI datasets in heterogenous AD cohorts, both in research and clinical settings.

scMultiMap: Cell-type-specific mapping of enhancers and target genes from single-cell multimodal data

Mapping enhancers and target genes in disease-related cell types provides critical insights into the functional mechanisms of genome-wide association studies (GWAS) variants. Single-cell multimodal data, which measure gene expression and chromatin accessibility in the same cells, enable the cell-type-specific inference of enhancer-gene pairs. However, this task is challenged by high data sparsity, sequencing depth variation, and the computational burden of analyzing a large number of pairs. We introduce scMultiMap, a statistical method that infers enhancer-gene association from sparse multimodal counts using a joint latent-variable model. It adjusts for technical confounding, permits fast moment-based estimation and provides analytically derived p-values. In blood and brain data, scMultiMap shows appropriate type I error control, high statistical power, and computational efficiency (1% of existing methods). When applied to Alzheimer's disease (AD) data, scMultiMap gives the highest heritability enrichment in microglia and reveals insights into the regulatory mechanisms of AD GWAS variants.

A 3D human iPSC-derived multi-cell type neurosphere system to model cellular responses to chronic amyloidosis

BACKGROUND

Alzheimer's disease (AD) is characterized by progressive amyloid beta (Aβ) deposition in the brain, with eventual widespread neurodegeneration. While the cell-specific molecular signature of end-stage AD is reasonably well characterized through autopsy material, less is known about the molecular pathways in the human brain involved in the earliest exposure to Aβ. Human model systems that not only replicate the pathological features of AD but also the transcriptional landscape in neurons, astrocytes and microglia are crucial for understanding disease mechanisms and for identifying novel therapeutic targets.

METHODS

In this study, we used a human 3D iPSC-derived neurosphere model to explore how resident neurons, microglia and astrocytes and their interplay are modified by chronic amyloidosis induced over 3-5 weeks by supplementing media with synthetic Aβ1 - 42 oligomers. Neurospheres under chronic Aβ exposure were grown with or without microglia to investigate the functional roles of microglia. Neuronal activity and oxidative stress were monitored using genetically encoded indicators, including GCaMP6f and roGFP1, respectively. Single nuclei RNA sequencing (snRNA-seq) was performed to profile Aβ and microglia driven transcriptional changes in neurons and astrocytes, providing a comprehensive analysis of cellular responses.

RESULTS

Microglia efficiently phagocytosed Aβ inside neurospheres and significantly reduced neurotoxicity, mitigating amyloidosis-induced oxidative stress and neurodegeneration following different exposure times to Aβ. The neuroprotective effects conferred by the presence of microglia was associated with unique gene expression profiles in astrocytes and neurons, including several known AD-associated genes such as APOE. These findings reveal how microglia can directly alter the molecular landscape of AD.

CONCLUSIONS

Our human 3D neurosphere culture system with chronic Aβ exposure reveals how microglia may be essential for the cellular and transcriptional responses in AD pathogenesis. Microglia are not only neuroprotective in neurospheres but also act as key drivers of Aβ-dependent APOE expression suggesting critical roles for microglia in regulating APOE in the AD brain. This novel, well characterized, functional in vitro platform offers unique opportunities to study the roles and responses of microglia to Aβ modelling key aspects of human AD. This tool will help identify new therapeutic targets, accelerating the transition from discovery to clinical applications.

Identification of markers for neurescence through transcriptomic profiling of postmortem human brains

Neuronal senescence (i.e., neurescent) is an important hallmark of aging and neurodegeneration, but it remains poorly characterized in the human brain due to the lack of reliable markers. This study aimed to identify neurescent markers based on single-nucleus transcriptome data from postmortem human prefrontal cortex. Using an eigengene approach, we integrated three gene panels: a) SenMayo, b) Canonical Senescence Pathway (CSP), and c) Senescence Initiating Pathway (SIP), to identify neurescent signatures. We found that paired markers outperform single markers; for instance, by combining CDKN2D and ETS2 in a decision tree, a high accuracy of 99% and perfect specificity (100%) were achieved in distinguishing neurescent. Differential expression analyses identified 324 genes that are overexpressed in neurescent. These genes showed significant associations with important neurodegeneration-related pathways including Alzheimer's disease, Parkinson's disease, and Huntington's disease. Interestingly, several of these overexpressed genes are linked to mitochondrial dysfunction and cytoskeletal dysregulation. These findings provide valuable insights into the complexities of neurescent, emphasizing the need for further exploration of histologically viable markers and validation in broader datasets.

Silencer variants are key drivers of gene upregulation in Alzheimer's disease

Alzheimer's disease (AD), particularly late-onset AD, stands as the most prevalent neurodegenerative disorder globally. Owing to its substantial heritability, genetic studies have emerged as indispensable for elucidating genes and biological pathways driving AD onset and progression. However, genetic and molecular mechanisms underlying AD remain poorly defined, largely due to the pronounced heterogeneity of AD and the intricate interactions among AD genetic factors. Notably, approximately 90% of AD-associated genetic variants reside in intronic and intergenic regions, yet their functional significance has remained largely uncharacterized. To address this challenge, we developed a deep learning framework combining bulk and single-cell epigenomic data to evaluate the regulatory potential (i.e., silencing and activating strength) of noncoding AD variants in the dorsolateral prefrontal cortex (DLPFCs) and its major cell types. This model identified 1,457 silencer and 3,084 enhancer AD-associated variants in the DLPFC and binned them into silencer variants only (SL), enhancer variants only (EN), or both variant types (ENSL) classes. Each class exerts distinct cellular and molecular influences on AD pathogenesis. EN loci predominantly regulate housekeeping metabolic processes, whereas SL loci (including the genes MS4A6A , TREM2 , USP6NL , HLA-D ) are selectively linked to immune responses. Notably, 71% of these genes are significantly upregulated in AD and pro-inflammation-stimulated microglia. Furthermore, genes associated with SL loci are, in neuronal cells, often responsive to glutamate receptor antagonists (e.g, NBQX) and anti-inflammatory perturbagens (such as D-64131), the compound classes known for reducing the AD risk. ENSL loci, in contrast, are uniquely implicated in memory maintenance, neurofibrillary tangle assembly, and are also shared by other neurological disorders such as Parkinson's disease and schizophrenia. Key genes in this class of loci, such as MAPT , CR1/2 , and CLU , are frequently upregulated in AD subtypes with hyperphosphorylated tau aggregates. Critically, our model can accurately predict the impact of regulatory variants, with an average Pearson correlation coefficient of 0.54 and a directional concordance rate of 70% between our predictions and experimental outcomes. This model identified rs636317 as a causal AD variant in the MS4A locus, distinguishing it from the 7bp-away allele-neutral variant rs636341. Similarly, rs7922621 was prioritized over its 54-bp-away allele-neutral rs7901634 in the TSPAN14 locus. Additional causal variants include rs6701713 in the CR1 locus, and rs28834970 and rs755951 in the PTK2B locus. Collectively, this work advances our understanding of the regulatory landscape of AD-associated genetic variants, providing a framework to explore their functional roles in the pathogenesis of this complex disease.

Genetic risk in endolysosomal network genes correlates with endolysosomal dysfunction across neural cell types in Alzheimer's disease

Late-onset Alzheimer's disease (LOAD) has a complex genomic architecture with risk variants in multiple pathways, including the endolysosomal network (ELN). Whether genetic risk in specific pathways correlates with corresponding biological dysfunction remains largely unknown. We developed an endolysosomal pathway-specific polygenic risk score (ePRS) using 13 established AD GWAS loci containing ELN genes. We investigated the association between ePRS and AD neuropathology, then examined cell-specific endolysosomal morphology and transcriptomic profiles in post-mortem dorsolateral prefrontal cortex samples from donors stratified by ePRS burden. We found that the ePRS was significantly associated with AD diagnosis and neuropathological measures, comparable to a pathway-agnostic PRS despite representing far fewer loci. High ePRS correlated with increased neuronal endosome volume, number and perinuclear aggregation, as well as enlarged microglial lysosomes, independent of AD pathology. Single-nucleus RNA sequencing revealed cell-type transcriptomic changes associated with ePRS status, including glutamatergic signaling, protein homeostasis, responses to DNA damage and immune function. Neurons, astrocytes, oligodendrocytes, and microglia showed varied gene expression patterns associated with ePRS burden. Conclusions: This study provides evidence that AD genetic risk variants harboring ELN genes correlate with endolysosomal dysfunction in human brain tissue. These findings suggest that pathway-specific genetic risk contributes to corresponding cellular pathology in AD and nominates candidate mechanisms by which ELN AD variants contribute to pathogenesis.

Regional susceptibility of PV interneurons in an hAPP-KI mouse model of Alzheimer's disease pathology

Early-stage Alzheimer's pathology correlates with disrupted neuronal excitability, which can drive network and cognitive dysfunction even prior to neurodegeneration. However, the emergence and extent of these changes may vary by brain region and cell types situated in those regions. Here we aimed to investigate the effects of AD pathology on different neuron subtypes in both the entorhinal cortex, a region with enhanced pathology in early AD, and the primary visual cortex, a relatively unaffected region in early-stage AD. We designed and employed a semi-automated patch clamp electrophysiology apparatus to record from fast-spiking parvalbumin interneurons and excitatory neurons in these regions, recording from over 150 cells in young adult APP-KI mice. In entorhinal cortex, amyloid overproduction resulted in PV interneuron hypoexcitability, whereas excitatory neurons were concurrently hyperexcitable. Conversely, neurons of either subclass were largely unaffected in the visual cortex. Together, these findings suggest that fast-spiking parvalbumin interneurons in the entorhinal cortex, but not in the visual cortex, play an integral role in AD progression.

Astrocyte and oligodendrocyte pathology in Alzheimer's disease

Astrocytes and oligodendrocytes, once considered passive support cells, are now recognized as active participants in the pathogenesis of Alzheimer's disease. Emerging evidence highlights the critical role that these glial cells play in the pathological features of Alzheimer's, including neuroinflammation, excitotoxicity, synaptic dysfunction, and myelin degeneration, which contribute to neurodegeneration and cognitive decline. Here, we review the current understanding of astrocyte and oligodendrocyte pathology in Alzheimer's disease and highlight research that supports the therapeutic potential of modulating astrocyte and oligodendrocyte functions to treat Alzheimer's disease.

Longitudinal analysis of a dominantly inherited Alzheimer disease mutation carrier protected from dementia

We conducted an in-depth longitudinal study on an individual carrying the presenilin 2 p.Asn141Ile mutation, traditionally associated with dominantly inherited Alzheimer's disease (AD), who has remarkably remained asymptomatic past the expected age of clinical onset. This study combines genetic, neuroimaging and biomarker analyses to explore the underpinnings of this resilience. Unlike typical progression in dominantly inherited AD, tau pathology in this case was confined to the occipital region without evidence of spread, potentially explaining the preservation of cognitive functions. Genetic analysis revealed several variants that, although not previously associated with protection against AD, suggest new avenues for understanding disease resistance. Notably, environmental factors such as significant heat exposure and a unique proteomic profile rich in heat shock proteins might indicate adaptive mechanisms contributing to the observed phenotype. This case underscores the complexity of Alzheimer's pathology and suggests that blocking tau deposition could be a promising target for therapeutic intervention. The study highlights the need for further research to identify and validate the mechanisms that could inhibit or localize tau pathology as a strategy to mitigate or delay the onset of Alzheimer's dementia.

Decoding microglial immunometabolism: a new frontier in Alzheimer's disease research

Alzheimer's disease (AD) involves a dynamic interaction between neuroinflammation and metabolic dysregulation, where microglia play a central role. These immune cells undergo metabolic reprogramming in response to AD-related pathology, with key genes such as TREM2, APOE, and HIF-1α orchestrating these processes. Microglial metabolism adapts to environmental stimuli, shifting between oxidative phosphorylation and glycolysis. Hexokinase-2 facilitates glycolytic flux, while AMPK acts as an energy sensor, coordinating lipid and glucose metabolism. TREM2 and APOE regulate microglial lipid homeostasis, influencing Aβ clearance and immune responses. LPL and ABCA7, both associated with AD risk, modulate lipid processing and cholesterol transport, linking lipid metabolism to neurodegeneration. PPARG further supports lipid metabolism by regulating microglial inflammatory responses. Amino acid metabolism also contributes to microglial function. Indoleamine 2,3-dioxygenase controls the kynurenine pathway, producing neurotoxic metabolites linked to AD pathology. Additionally, glucose-6-phosphate dehydrogenase regulates the pentose phosphate pathway, maintaining redox balance and immune activation. Dysregulated glucose and lipid metabolism, influenced by genetic variants such as APOE4, impair microglial responses and exacerbate AD progression. Recent findings highlight the interplay between metabolic regulators like REV-ERBα, which modulates lipid metabolism and inflammation, and Syk, which influences immune responses and Aβ clearance. These insights offer promising therapeutic targets, including strategies aimed at HIF-1α modulation, which could restore microglial function depending on disease stage. By integrating metabolic, immune, and genetic factors, this review underscores the importance of microglial immunometabolism in AD. Targeting key metabolic pathways could provide novel therapeutic strategies for mitigating neuroinflammation and restoring microglial function, ultimately paving the way for innovative treatments in neurodegenerative diseases.

Sex-specific Associations of Gene Expression with Alzheimer's Disease Neuropathology and Ante-mortem Cognitive Performance

The biological mechanisms underlying the increased prevalence of Alzheimer's disease (AD) in women remain undefined. While previous case/control studies have identified sex-biased molecular pathways, the sex-specific relationships between gene expression and AD endophenotypes, particularly involving sex chromosomes, are underexplored. With bulk transcriptomic data across 3 brain regions from 767 decedents, we investigated sex-specific associations between gene expression and post-mortem β-amyloid and tau, as well as antemortem longitudinal cognition. Among 23,118 significant gene associations, 10% were sex-specific, with 73% of these identified in females and primarily associated with tau tangles and longitudinal cognition (90%). Notably, four X-linked genes, MCF2, HDAC8, FTX, and SLC10A3, demonstrated significant sex differences in their associations with AD endophenotypes (i.e., significant sex × gene interaction). Our results also uncovered sex-specific biological pathways, including a female-specific role of neuroinflammation and neuronal development, underscoring the importance of sex-aware analyses to advance precision medicine approaches in AD.

GFAP mutation and astrocyte dysfunction lead to a neurodegenerative profile with impaired synaptic plasticity and cognitive deficits in a rat model of Alexander disease

Alexander disease (AxD) is a rare neurological disorder caused by dominant gain-of-function mutations in the gene for glial acidic fibrillary protein (GFAP). Expression of mutant protein results in astrocyte dysfunction that ultimately leads to developmental delay, failure to thrive, and intellectual and motor impairment. The disease is typically fatal, and at present there are no preventative or effective treatments. To gain a better understanding of the link between astrocyte dysfunction and behavioral deficits in AxD we recently developed a rat model that recapitulates many of the clinical features of the disease, including failure to thrive, motor impairment, and white matter deficits. In the present study, we show that both male and female AxD model rats exhibit a neurodegenerative profile with a progressive neuroinflammatory response combined with reduced expression of synaptic and mitochondrial proteins. Consistent with these results AxD rats show reduced hippocampal long-term potentiation and are cognitively impaired, as demonstrated by poor performance in the Barnes maze and novel object recognition tests. The AxD rat provides a novel model in which to investigate the impact of astrocyte pathology on central nervous system function and provides an essential platform for further development of effective treatments for AxD and potentially other neurodegenerative diseases with astrocyte pathology.Significance Statement Alexander disease (AxD) is a fatal neurodegenerative disorder caused by gain-of-function GFAP mutations. We recently developed a Gfap +/R237H rat model which demonstrates hallmark astrocyte pathology, myelin deficits, and motor impairment. Here, we show that Gfap +/R237H rats also exhibit reduced synaptic plasticity and cognitive deficits as additional clinically relevant phenotypes, further demonstrating its utility as a model. Hippocampal transcriptomic analysis in young adult animals reveals a neurodegenerative signature with an innate immune response and loss of synaptic and metabolic gene expression, features that are typically associated with chronic diseases of aging. These results reveal mechanisms by which astrocyte dysfunction leads to learning and memory deficits in AxD and perhaps contributes to other diseases such as Alzheimer's and Parkinson's.

Differential Transcriptional Programs Reveal Modular Network Rearrangements Associated with Late-Onset Alzheimer's Disease

Alzheimer's disease (AD) is a complex, genetically heterogeneous disorder. The diverse phenotypes associated with AD result from interactions between genetic and environmental factors, influencing multiple biological pathways throughout disease progression. Network-based approaches offer a way to assess phenotype-specific states. In this study, we calculated key network metrics to characterize the network transcriptional structure and organization in LOAD, focusing on genes and pathways implicated in AD pathology within the dorsolateral prefrontal cortex (DLPFC). Our findings revealed disease-specific coexpression markers associated with diverse metabolic functions. Additionally, significant differences were observed at both the mesoscopic and local levels between AD and control networks, along with a restructuring of gene coexpression and biological functions into distinct transcriptional modules. These results show the molecular reorganization of the transcriptional program occurring in LOAD, highlighting specific adaptations that may contribute to or result from cellular responses to pathological stressors. Our findings may support the development of a unified model for the causal mechanisms of AD, suggesting that its diverse manifestations arise from multiple pathways working together to produce the disease's complex clinical patho-phenotype.

CRISPRi-based screens in iAssembloids to elucidate neuron-glia interactions

The complexity of the human brain makes it challenging to understand the molecular mechanisms underlying brain function. Genome-wide association studies have uncovered variants associated with neurological phenotypes. Single-cell transcriptomics have provided descriptions of changes brain cells undergo during disease. However, these approaches do not establish molecular mechanism. To facilitate the scalable interrogation of causal molecular mechanisms in brain cell types, we developed a 3D co-culture system of induced pluripotent stem cell (iPSC)-derived neurons and glia, termed iAssembloids. Using iAssembloids, we ask how glial and neuronal cells interact to control neuronal death and survival. Our CRISPRi-based screens identified that GSK3β inhibits the protective NRF2-mediated oxidative stress response elicited by high neuronal activity. We then investigate the role of APOE-ε4, a risk variant for Alzheimer's disease, on neuronal survival. We find that APOE-ε4-expressing astrocytes may promote neuronal hyperactivity as compared with APOE-ε3-expressing astrocytes. This platform allows for the unbiased identification of mechanisms of neuron-glia cell interactions.

Biases in machine-learning models of human single-cell data

Recent machine-learning (ML)-based advances in single-cell data science have enabled the stratification of human tissue donors at single-cell resolution, promising to provide valuable diagnostic and prognostic insights. However, such insights are susceptible to biases. Here we discuss various biases that emerge along the pipeline of ML-based single-cell analysis, ranging from societal biases affecting whose samples are collected, to clinical and cohort biases that influence the generalizability of single-cell datasets, biases stemming from single-cell sequencing, ML biases specific to (weakly supervised or unsupervised) ML models trained on human single-cell samples and biases during the interpretation of results from ML models. We end by providing methods for single-cell data scientists to assess and mitigate biases, and call for efforts to address the root causes of biases.

Systematic review and meta-analysis of bulk RNAseq studies in human Alzheimer's disease brain tissue

We systematically reviewed and meta-analyzed bulk RNA sequencing (RNAseq) studies comparing Alzheimer's disease (AD) patients to controls in human brain tissue. We searched PubMed, Web of Science, and Scopus for human brain bulk RNAseq studies, excluding re-analyses and studies limited to small RNAs or gene panels. We developed 10 criteria for quality assessment and performed a meta-analysis on three high-quality datasets. Of 3266 records, 24 qualified for the systematic review, and one study with three datasets qualified for the meta-analysis. The meta-analysis identified 571 differentially expressed genes (DEGs) in the temporal lobe and 189 in the frontal lobe, including CLU and GFAP. Pathway analysis suggested reactivation of developmental processes in the adult AD brain. Limited data availability constrained the meta-analysis. These findings underscore the need for rigorous methods in AD transcriptomic research to better identify transcriptomic changes and advance biomarker and therapeutic development. This review is registered in PROSPERO (CRD42023466522).

HIGHLIGHTS

Comprehensive review: Conducted the first systematic review and meta-analysis of bulk RNA sequencing (RNAseq) studies comparing Alzheimer's disease (AD) patients with non-demented controls using primary human brain tissue.

KEY FINDINGS

Identified 571 differentially expressed genes (DEGs) in the temporal lobe and 189 in the frontal lobe of patients with AD, revealing potential therapeutic targets. Pathway discovery: Highlighted key overlapping pathways such as "tube morphogenesis" and "neuroactive ligand-receptor interaction" that may play critical roles in AD.

QUALITY ASSESSMENT

Emphasized the importance of methodological rigor in transcriptomic studies, including quality assessment tools to guide future research in AD.

STUDY LIMITATION

Acknowledged limited access to complete data tables and lack of diversity in existing datasets, which constrained some of the analysis.

New Multiomic Studies Shed Light on Cellular Diversity and Neuronal Susceptibility in Parkinson's Disease

Parkinson's disease is a complex neurodegenerative disorder characterized by degeneration of dopaminergic neurons, with patients manifesting varying motor and nonmotor symptoms. Previous studies using single-cell RNA sequencing in rodent models and humans have identified distinct heterogeneity of neurons and glial cells with differential vulnerability. Recent studies have increasingly leveraged multiomics approaches, including spatial transcriptomics, epigenomics, and proteomics, in the study of Parkinson's disease, providing new insights into pathogenic mechanisms. Continued advancements in experimental technologies and sophisticated computational tools will be essential in uncovering a network of neuronal vulnerability and prioritizing disease modifiers for novel therapeutics development. © 2025 International Parkinson and Movement Disorder Society.

Biomarker Identification for Alzheimer's Disease Using a Multi-Filter Gene Selection Approach

There is still a lack of effective therapies for Alzheimer's disease (AD), the leading cause of dementia and cognitive decline. Identifying reliable biomarkers and therapeutic targets is crucial for advancing AD research. In this study, we developed an aggregative multi-filter gene selection approach to identify AD biomarkers. This method integrates hub gene ranking techniques, such as degree and bottleneck, with feature selection algorithms, including Random Forest and Double Input Symmetrical Relevance, and applies ranking aggregation to improve accuracy and robustness. Five publicly available AD-related microarray datasets (GSE48350, GSE36980, GSE132903, GSE118553, and GSE5281), covering diverse brain regions like the hippocampus and frontal cortex, were analyzed, yielding 803 overlapping differentially expressed genes from 464 AD and 492 normal cases. An independent dataset (GSE109887) was used for external validation. The approach identified 50 prioritized genes, achieving an AUC of 86.8 in logistic regression on the validation dataset, highlighting their predictive value. Pathway analysis revealed involvement in critical biological processes such as synaptic vesicle cycles, neurodegeneration, and cognitive function. These findings provide insights into potential therapeutic targets for AD.

Type 3 diabetes and metabolic reprogramming of brain neurons: causes and therapeutic strategies

Abnormal glucose metabolism inevitably disrupts normal neuronal function, a phenomenon widely observed in Alzheimer's disease (AD). Investigating the mechanisms of metabolic adaptation during disease progression has become a central focus of research. Considering that impaired glucose metabolism is closely related to decreased insulin signaling and insulin resistance, a new concept "type 3 diabetes mellitus (T3DM)" has been coined. T3DM specifically refers to the brain's neurons becoming unresponsive to insulin, underscoring the strong link between diabetes and AD. Recent studies reveal that during brain insulin resistance, neurons exhibit mitochondrial dysfunction, reduced glucose metabolism, and elevated lactate levels. These findings suggest that impaired insulin signaling caused by T3DM may lead to a compensatory metabolic shift in neurons toward glycolysis. Consequently, this review aims to explore the underlying causes of T3DM and elucidate how insulin resistance drives metabolic reprogramming in neurons during AD progression. Additionally, it highlights therapeutic strategies targeting insulin sensitivity and mitochondrial function as promising avenues for the successful development of AD treatments.

Reduced protein solubility - cause or consequence in amyloid disease?

In this perspective, we ask the question whether the apparently lower solubility of specific proteins in amyloid disease is a cause or consequence of the protein deposition seen in such diseases. We focus on Alzheimer's disease and start by reviewing the experimental evidence of disease-associated reduction in the measured concentration of amyloid β peptide, Aβ42, in cerebrospinal fluid. We propose a series of possible physicochemical explanations for these observations. These include a reduced solubility, a reduced apparent solubility, as well as a long-lived metastable state manifested in healthy individuals as a free concentration of Aβ42 in the solution phase above the solubility limit. For each scenario, we discuss whether it is most likely a cause or a consequence of the observed protein deposition in the disease.

Powerful and accurate case-control analysis of spatial molecular data with deep learning-defined tissue microniches

As spatial molecular data grow in scope and resolution, there is a pressing need to identify key spatial structures associated with disease. Current approaches often rely on hand-crafted features such as local abundances of manually annotated, discrete cell types, which may overlook important signals. Here we introduce variational inference-based microniche analysis (VIMA), a method that combines deep learning with principled statistics to discover associated spatial features with greater flexibility and precision. VIMA uses a variational autoencoder to extract numerical "fingerprints" from small tissue patches that capture their biological content. It uses these fingerprints to define a large number of "microniches" - small, potentially overlapping groups of tissue patches with highly similar biology that span multiple samples. It then uses rigorous statistics to identify microniches whose abundance correlates with case-control status. We show in simulations that VIMA is well calibrated and more powerful and accurate than other approaches. We then apply VIMA to a 140-gene spatial transcriptomics dataset in Alzheimer's dementia, a 54-marker CO-Detection by indEXing (CODEX) dataset in ulcerative colitis (UC), and a 7-marker immunohistochemistry dataset in rheumatoid arthritis (RA), in each case recapitulating known biology and identifying novel spatial features of disease.

Cell-type specific profiling of human entorhinal cortex at the onset of Alzheimer's disease neuropathology

Neurons located in layer II of the entorhinal cortex (ECII) are the primary site of pathological tau accumulation and neurodegeneration at preclinical stages of Alzheimer's disease (AD). Exploring the alterations that underlie the early degeneration of these cells is essential to develop therapies that curb the disease before symptom onset. Here we performed cell-type specific profiling of human EC at the onset of AD neuropathology. We identify an early response to amyloid pathology by microglia and oligodendrocytes. Importantly, we provide the first insight into neuronal alterations that coincide with incipient tau pathology: the signaling pathway for Reelin, recently shown to be a major AD resilience gene is dysregulated in ECII neurons, while the secreted synaptic organizer molecules NPTX2 and CBLN4, emerging AD biomarkers, are downregulated in surrounding neurons. By uncovering the complex multicellular landscape of EC at these early AD stages, this study paves the way for detailed characterization of the mechanisms governing NFT formation and opens long-needed novel therapeutic avenues.

Gene module-trait network analysis uncovers cell type specific systems and genes relevant to Alzheimer's Disease

Alzheimer's Disease (AD) is marked by the accumulation of pathology, neuronal loss, and gliosis and frequently accompanied by cognitive decline. Understanding brain cell interactions is key to identifying new therapeutic targets to slow its progression. Here, we used systems biology methods to analyze single-nucleus RNA sequencing (snRNASeq) data generated from dorsolateral prefrontal cortex (DLPFC) tissues of 424 participants in the Religious Orders Study or the Rush Memory and Aging Project (ROSMAP). We identified modules of co-regulated genes in seven major cell types, assigned them to coherent cellular processes, and assessed which modules were associated with AD traits such as cognitive decline, tangle density, and amyloid-β deposition. Coexpression network structure was conserved in the majority of modules across cell types, but we also found distinct communities with altered connectivity, especially when compared to bulk RNASeq, suggesting cell-specific gene co-regulation. These coexpression modules can also capture signatures of cell subpopulations and be influenced by cell proportions. Using a Bayesian network framework, we modeled the direction of relationships between the modules and AD progression. We highlight two key modules, a microglia module (mic_M46), associated with tangles; and an astrocyte module (ast_M19), associated with cognitive decline. Our work provides cell-specific molecular networks modeling the molecular events leading to AD.

Synapse vulnerability and resilience underlying Alzheimer's disease

Synapse preservation is key for healthy cognitive ageing, and synapse loss represents a critical anatomical basis of cognitive dysfunction in Alzheimer's disease (AD), predicting dementia onset, severity, and progression. Synapse loss is viewed as a primary pathologic event, preceding neuronal loss and brain atrophy in AD. Synapses may, therefore, represent one of the earliest and clinically most meaningful targets of the neuropathologic processes driving AD dementia. The synapse loss in AD is highly selective and targets particularly vulnerable synapses while leaving others, termed resilient, largely unaffected. Yet, the anatomic and molecular hallmarks of the vulnerable and resilient synapse populations and their association with AD neuropathologic changes (e.g. amyloid-β plaques and tau tangles) and memory dysfunction remain poorly understood. Characterising the selectively vulnerable and resilient synapses in AD may be key to understanding the mechanisms of cognitive preservation versus loss and enable the development of robust biomarkers and disease-modifying therapies for dementia.

Molecular and cellular characteristics of cerebrovascular cell types and their contribution to neurodegenerative diseases

Many diseases and disorders of the nervous system suffer from a lack of adequate therapeutics to halt or slow disease progression, and to this day, no cure exists for any of the fatal neurodegenerative diseases. In part this is due to the incredible diversity of cell types that comprise the brain, knowledge gaps in understanding basic mechanisms of disease, as well as a lack of reliable strategies for delivering new therapeutic modalities to affected areas. With the advent of single cell genomics, it is now possible to interrogate the molecular characteristics of diverse cell populations and their alterations in diseased states. More recently, much attention has been devoted to cell populations that have historically been difficult to profile with bulk single cell technologies. In particular, cell types that comprise the cerebrovasculature have become increasingly better characterized in normal and neurodegenerative disease contexts. In this review, we describe the current understanding of cerebrovasculature structure, function, and cell type diversity and its role in the mechanisms underlying various neurodegenerative diseases. We focus on human and mouse cerebrovasculature studies and discuss both origins and consequences of cerebrovascular dysfunction, emphasizing known cell type-specific vulnerabilities in neuronal and cerebrovascular cell populations. Lastly, we highlight how novel insights into cerebrovascular biology have impacted the development of modern therapeutic approaches and discuss outstanding questions in the field.

Molecular hallmarks of excitatory and inhibitory neuronal resilience and resistance to Alzheimer's disease

Background

A significant proportion of individuals maintain healthy cognitive function despite having extensive Alzheimer's disease (AD) pathology, known as cognitive resilience. Understanding the molecular mechanisms that protect these individuals can identify therapeutic targets for AD dementia. This study aims to define molecular and cellular signatures of cognitive resilience, protection and resistance, by integrating genetics, bulk RNA, and single-nucleus RNA sequencing data across multiple brain regions from AD, resilient, and control individuals.

Methods

We analyzed data from the Religious Order Study and the Rush Memory and Aging Project (ROSMAP), including bulk (n=631) and multi-regional single nucleus (n=48) RNA sequencing. Subjects were categorized into AD, resilient, and control based on β-amyloid and tau pathology, and cognitive status. We identified and prioritized protected cell populations using whole genome sequencing-derived genetic variants, transcriptomic profiling, and cellular composition distribution.

Results

Transcriptomic results, supported by GWAS-derived polygenic risk scores, place cognitive resilience as an intermediate state in the AD continuum. Tissue-level analysis revealed 43 genes enriched in nucleic acid metabolism and signaling that were differentially expressed between AD and resilience. Only GFAP (upregulated) and KLF4 (downregulated) showed differential expression in resilience compared to controls. Cellular resilience involved reorganization of protein folding and degradation pathways, with downregulation of Hsp90 and selective upregulation of Hsp40, Hsp70, and Hsp110 families in excitatory neurons. Excitatory neuronal subpopulations in the entorhinal cortex (ATP8B1+ and MEF2Chigh) exhibited unique resilience signaling through neurotrophin (modulated by LINGO1) and angiopoietin (ANGPT2/TEK) pathways. We identified MEF2C, ATP8B1, and RELN as key markers of resilient excitatory neuronal populations, characterized by selective vulnerability in AD. Protective rare variant enrichment highlighted vulnerable populations, including somatostatin (SST) inhibitory interneurons, validated through immunofluorescence showing co-expression of rare variant associated RBFOX1 and KIF26B in SST+ neurons in the dorsolateral prefrontal cortex. The maintenance of excitatory-inhibitory balance emerges as a key characteristic of resilience.

Conclusions

We identified molecular and cellular hallmarks of cognitive resilience, an intermediate state in the AD continuum. Resilience mechanisms include preservation of neuronal function, maintenance of excitatory/inhibitory balance, and activation of protective signaling pathways. Specific excitatory neuronal populations appear to play a central role in mediating cognitive resilience, while a subset of vulnerable SST interneurons likely provide compensation against AD-associated dysregulation. This study offers a framework to leverage natural protective mechanisms to mitigate neurodegeneration and preserve cognition in AD.

LncRNA 3222401L13Rik Is Upregulated in Aging Astrocytes and Regulates Neuronal Support Function Through Interaction with Npas3

Aging leads to cognitive decline and increased risk of neurodegenerative diseases. While molecular changes in central nervous system (CNS) cells contribute to this decline, the mechanisms are not fully understood. Long non-coding RNAs (lncRNAs) are key regulators of cellular functions. Background/Objectives: The roles of lncRNAs in aging, especially in glial cells, are not well characterized. Methods: We investigated lncRNA expression in non-neuronal cells from aged mice and identified 3222401L13Rik, a previously unstudied lncRNA, as upregulated in astrocytes during aging. Results: Knockdown of 3222401L13Rik in primary astrocytes revealed its critical role in regulating genes for neuronal support and synapse organization, a function conserved in human iPSC-derived astrocytes. A 3222401L13Rik interacts with the transcription factor Neuronal PAS Domain Protein 3 (Npas3), and overexpression of Npas3 rescues deficits in astrocytes lacking 3222401L13Rik. Conclusions: These data suggest that 3222401L13Rik upregulation may help delay age-related cognitive decline.

Sex-specific Associations of Gene Expression with Alzheimer's Disease Neuropathology and Ante-mortem Cognitive Performance

The biological mechanisms underlying women's increased Alzheimer's disease (AD) prevalence remain undefined. Previous case/control studies have identified sex-biased molecular pathways, but sex-specific relationships between gene expression and AD endophenotypes, particularly sex chromosomes, are underexplored. With bulk transcriptomic data across 3 brain regions from 767 decedents, we investigated sex-specific associations between gene expression and post-mortem β-amyloid and tau as well as antemortem longitudinal cognition. Of 23,118 significant gene associations, 10% were significant in one sex and not the other (sex-specific). Most sex-specific gene associations were identified in females (73%) and associated with tau tangles and longitudinal cognition (90%). Four X-linked genes, MCF2, HDAC8, FTX, and SLC10A3, demonstrated significant sex differences in their associations with AD endophenotypes (i.e., significant sex x gene interaction). Our results also uncovered sex-specific biological pathways, including a female-specific role of neuroinflammation and neuronal development, reinforcing the potential for sex-aware analyses to enhance precision medicine approaches in AD.

Rhythmic astrocytic GABA production synchronizes neuronal circadian timekeeping in the suprachiasmatic nucleus

Astrocytes of the suprachiasmatic nucleus (SCN) can regulate sleep-wake cycles in mammals. However, the nature of the information provided by astrocytes to control circadian patterns of behavior is unclear. Neuronal circadian activity across the SCN is organized into spatiotemporal waves that govern seasonal adaptations and timely engagement of behavioral outputs. Here, we show that astrocytes across the mouse SCN exhibit instead a highly uniform, pulse-like nighttime activity. We find that rhythmic astrocytic GABA production via polyamine degradation provides an inhibitory nighttime tone required for SCN circuit synchrony, thereby acting as an internal astrocyte zeitgeber (or "astrozeit"). We further identify synaptic GABA and astrocytic GABA as two key players underpinning coherent spatiotemporal circadian patterns of SCN neuronal activity. In describing a new mechanism by which astrocytes contribute to circadian timekeeping, our work provides a general blueprint for understanding how astrocytes encode temporal information underlying complex behaviors in mammals.

Approaches for studying neuroimmune interactions in Alzheimer's disease

Peripheral immune cells play an important role in the pathology of Alzheimer's disease (AD), impacting processes such as amyloid and tau protein aggregation, glial activation, neuronal integrity, and cognitive decline. Here, we examine cutting-edge strategies - encompassing animal and cellular models - used to investigate the roles of peripheral immune cells in AD. Approaches such as antibody-mediated depletion, genetic ablation, and bone marrow chimeras in mouse models have been instrumental in uncovering T, B, and innate immune cell disease-modifying functions. However, challenges such as specificity, off-target effects, and differences between human and mouse immune systems underscore the need for more human-relevant models. Emerging multicellular models replicating critical aspects of human brain tissue and neuroimmune interactions increasingly offer fresh insights into the role of immune cells in AD pathogenesis. Refining these methodologies can deepen our understanding of immune cell contributions to AD and support the development of novel immune-related therapeutic interventions.

SMOC1 colocalizes with Alzheimer's disease neuropathology and delays Aβ aggregation

SMOC1 has emerged as one of the most significant and consistent new biomarkers of early Alzheimer's disease (AD). Recent studies show that SMOC1 is one of the earliest changing proteins in AD, with levels in the cerebrospinal fluid increasing many years before symptom onset. Despite this clear association with disease, little is known about the role of SMOC1 in AD or its function in the brain. Therefore, the aim of this study was to examine the distribution of SMOC1 in human AD brain tissue and to determine if SMOC1 influenced amyloid beta (Aβ) aggregation. The distribution of SMOC1 in human brain tissue was assessed in 3 brain regions (temporal cortex, hippocampus, and frontal cortex) using immunohistochemistry in a cohort of 73 cases encompassing advanced AD, mild cognitive impairment (MCI), preclinical AD, and cognitively normal controls. The Aβ- and phosphorylated tau-interaction with SMOC1 was assessed in control, MCI, and advanced AD human brain tissue using co-immunoprecipitation, and the influence of SMOC1 on Aβ aggregation kinetics was assessed using Thioflavin-T assays and electron microscopy. SMOC1 strongly colocalized with a subpopulation of amyloid plaques in AD (43.8 ± 2.4%), MCI (32.8 ± 5.4%), and preclinical AD (28.3 ± 6.4%). SMOC1 levels in the brain strongly correlated with plaque load, irrespective of disease stage. SMOC1 also colocalized with a subpopulation of phosphorylated tau aggregates in AD (9.6 ± 2.6%). Co-immunoprecipitation studies showed that SMOC1 strongly interacted with Aβ in human MCI and AD brain tissue and with phosphorylated tau in human AD brain tissue. Thioflavin-T aggregation assays showed that SMOC1 significantly delayed Aβ aggregation in a dose-dependent manner, and electron microscopy confirmed that the Aβ fibrils generated in the presence of SMOC1 had an altered morphology. Overall, our results emphasize the importance of SMOC1 in the onset and progression of AD and suggest that SMOC1 may influence pathology development in AD.

Spatial Transcriptomic Analysis Identifies a SERPINA3-Expressing Astrocytic State Associated with the Human Neuritic Plaque Microenvironment

Single-nucleus transcriptomic studies have revealed glial cell states associated with Alzheimer's disease; however, these nuclei are dissociated from the complex architecture of the human neocortex. Here, we successfully performed an unbiased distance-based analytic strategy on spatially-registered transcriptomic data. Leveraging immunohistochemistry in the same tissue section, our analyses prioritized SERPINA3 and other genes, such as metallothioneins, as altered in the vicinity of neuritic amyloid plaques. Results were validated at the protein level by immunofluorescence, highlighting that a reactive SERPINA3+ astrocyte subtype, Ast.5, plays a role in the plaque microenvironment.

Single cell variant to enhancer to gene map for coronary artery disease

Although genome wide association studies (GWAS) in large populations have identified hundreds of variants associated with common diseases such as coronary artery disease (CAD), most disease-associated variants lie within non-coding regions of the genome, rendering it difficult to determine the downstream causal gene and cell type. Here, we performed paired single nucleus gene expression and chromatin accessibility profiling from 44 human coronary arteries. To link disease variants to molecular traits, we developed a meta-map of 88 samples and discovered 11,182 single-cell chromatin accessibility quantitative trait loci (caQTLs). Heritability enrichment analysis and disease variant mapping demonstrated that smooth muscle cells (SMCs) harbor the greatest genetic risk for CAD. To capture the continuum of SMC cell states in disease, we used dynamic single cell caQTL modeling for the first time in tissue to uncover QTLs whose effects are modified by cell state and expand our insight into genetic regulation of heterogenous cell populations. Notably, we identified a variant in the COL4A1/COL4A2 CAD GWAS locus which becomes a caQTL as SMCs de-differentiate by changing a transcription factor binding site for EGR1/2. To unbiasedly prioritize functional candidate genes, we built a genome-wide single cell variant to enhancer to gene (scV2E2G) map for human CAD to link disease variants to causal genes in cell types. Using this approach, we found several hundred genes predicted to be linked to disease variants in different cell types. Next, we performed genome-wide Hi-C in 16 human coronary arteries to build tissue specific maps of chromatin conformation and link disease variants to integrated chromatin hubs and distal target genes. Using this approach, we show that rs4887091 within the ADAMTS7 CAD GWAS locus modulates function of a super chromatin interactome through a change in a CTCF binding site. Finally, we used CRISPR interference to validate a distal gene, AMOTL2, liked to a CAD GWAS locus. Collectively we provide a disease-agnostic framework to translate human genetic findings to identify pathologic cell states and genes driving disease, producing a comprehensive scV2E2G map with genetic and tissue level convergence for future mechanistic and therapeutic studies.

Systematic review and meta-analysis of bulk RNAseq studies in human Alzheimer's disease brain tissue

Objective

To systematically review and meta-analyze bulk RNA sequencing studies comparing Alzheimer's disease (AD) patients with controls in human brain tissue, assessing study quality and identifying key genes and pathways.

Methods

We searched PubMed, Web of Science, and Scopus on September 23, 2023, for studies using bulk RNAseq on primary human brain tissue from AD patients and controls. Excluded were non-primary tissue, re-analyses without new data, limited RNA types and gene panels. Quality was assessed with a 10-category tool. Meta-analysis used high-quality datasets.

Results

From 3,266 records, 24 studies met criteria. Meta-analysis found 571 differentially expressed genes (DEGs) in temporal lobe and 189 in frontal lobe; overlapping pathways included "Tube morphogenesis" and "Neuroactive ligand-receptor interaction."

Limitations

Study heterogeneity and limited data tables constrained the review.

Conclusions

Rigorous methods are vital in AD transcriptomic studies. Findings enhance understanding of transcriptomic changes, aiding biomarker and therapeutic development.

Registration

PROSPERO (CRD42023466522).

Molecular Signatures of Resilience to Alzheimer's Disease in Neocortical Layer 4 Neurons

Single-cell omics is advancing our understanding of selective neuronal vulnerability in Alzheimer's disease (AD), revealing specific subtypes that are either susceptible or resilient to neurodegeneration. Using single-nucleus and spatial transcriptomics to compare neocortical regions affected early (prefrontal cortex and precuneus) or late (primary visual cortex) in AD, we identified a resilient excitatory population in layer 4 of the primary visual cortex expressing RORB, CUX2, and EYA4. Layer 4 neurons in association neocortex also remained relatively preserved as AD progressed and shared overlapping molecular signatures of resilience. Early in the disease, resilient neurons upregulated genes associated with synapse maintenance, synaptic plasticity, calcium homeostasis, and neuroprotective factors, including GRIN2A, RORA, NRXN1, NLGN1, NCAM2, FGF14, NRG3, NEGR1, and CSMD1. We also identified KCNIP4, which encodes a voltage-gated potassium (Kv) channel-interacting protein that interacts with Kv4.2 channels and presenilins, as a key factor linked to resilience. KCNIP4 was consistently upregulated in the early stages of pathology. Furthermore, AAV-mediated overexpression of Kcnip4 in a humanized AD mouse model reduced the expression of the activity-dependent genes Arc and c-Fos, suggesting compensatory mechanisms against neuronal hyperexcitability. Our dataset provides a valuable resource for investigating mechanisms underlying resilience to neurodegeneration.

SMOC1 colocalizes with Alzheimer's disease neuropathology and delays Aβ aggregation

SMOC1 has emerged as one of the most significant and consistent new biomarkers of early Alzheimer's disease (AD). Recent studies show that SMOC1 is one of the earliest changing proteins in AD, with levels in the cerebrospinal fluid increasing many years before symptom onset. Despite this clear association with disease, little is known about the role of SMOC1 in AD or its function in the brain. Therefore, the aim of this study was to examine the distribution of SMOC1 in human AD brain tissue and to determine if SMOC1 influenced amyloid beta (Aβ) aggregation. The distribution of SMOC1 in human brain tissue was assessed in 3 brain regions (temporal cortex, hippocampus, frontal cortex) using immunohistochemistry in a cohort of 73 cases encompassing advanced AD, mild cognitive impairment (MCI), preclinical AD and cognitively normal controls. The Aβ- and phosphorylated tau-interaction with SMOC1 was assessed in control, MCI and advanced AD human brain tissue using co-immunoprecipitation, and the influence of SMOC1 on Aβ aggregation kinetics was assessed using Thioflavin T assays and electron microscopy. SMOC1 strongly colocalized with a subpopulation of amyloid plaques in AD (43.8±2.4%), MCI (32.8±5.4%) and preclinical AD (28.3±6.4%). SMOC1 levels in the brain strongly correlated with plaque load, irrespective of disease stage. SMOC1 also colocalized with a subpopulation of phosphorylated tau aggregates in AD (9.6±2.6%). Co-immunoprecipitation studies showed that SMOC1 strongly interacted with Aβ in human MCI and AD brain tissue and with phosphorylated tau in human AD brain tissue. Thioflavin T aggregation assays showed that SMOC1 significantly delayed Aβ aggregation in a dose-dependent manner, and electron microscopy confirmed that the Aβ fibrils generated in the presence of SMOC1 had an altered morphology. Overall, our results emphasize the importance of SMOC1 in the onset and progression of AD and suggest that SMOC1 may influence pathology development in AD.

Astrocyte transcriptomic analysis identifies glypican 5 downregulation as a contributor to synaptic dysfunction in Alzheimer's disease models

Synaptic dysfunction is an early feature in Alzheimer's disease (AD) and correlates with cognitive decline. Astrocytes are essential regulators of synapses, impacting synapse formation, maturation, elimination and function. To understand if synapse-supportive functions of astrocytes are altered in AD, we used astrocyte BacTRAP mice to generate a comprehensive dataset of hippocampal astrocyte transcriptional alterations in two mouse models of Alzheimer's pathology (APPswe/PS1dE9 and Tau P301S), characterizing sex and age-dependent changes. We found that astrocytes from both models downregulate genes important for synapse regulation and function such as the synapse-maturation factor Glypican 5. This transcriptional signature is shared with human post-mortem AD patients. Manipulating a key component of this signature by in vivo overexpression of Glypican 5 in astrocytes is sufficient to prevent early synaptic dysfunction and improve spatial learning in APPswe/PS1dE9 mice. These findings open new avenues to target astrocytic factors to mitigate AD synaptic dysfunction.

The YTHDF Proteins Shape the Brain Gene Signatures of Alzheimer's Disease

The gene signatures of Alzheimer's Disease (AD) brains reflect an output of a complex interplay of genetic, epigenetic, epi-transcriptomic, and post-transcriptional regulations. To identify the most significant factor that shapes the AD brain signature, we developed a machine learning model (DEcode-tree) to integrate cellular and molecular factors explaining differential gene expression in AD. Our model indicates that YTHDF proteins, the canonical readers of N6-methyladenosine RNA modification (m6A), are the most influential predictors of the AD brain signature. We then show that protein modules containing YTHDFs are downregulated in human AD brains, and knocking out YTHDFs in iPSC-derived neural cells recapitulates the AD brain gene signature in vitro . Furthermore, eCLIP-seq analysis revealed that YTHDF proteins influence AD signatures through both m6A-dependent and independent pathways. These results indicate the central role of YTHDF proteins in shaping the gene signature of AD brains.

Human Astrocytes Synchronize Neural Organoid Networks

Biological neural networks exhibit synchronized activity within and across interconnected regions of the central nervous system. Understanding how these coordinated networks are established and maintained may reveal therapeutic targets for neurodegeneration and neuromodulation. Here, we tested the influence of astrocytes upon synchronous network activity using human pluripotent stem cell-derived bioengineered neural organoids. This study revealed that astrocytes significantly increase activity within individual organoids and across long distances among numerous rapidly merged organoids via influencing synapses and bioenergetics. Treatment of amyloid protein inhibited synchronous activity during neurodegeneration, yet this can be rescued by propagating activity from neighboring networks. Altogether, this study identifies critical contributions of human astrocytes to biological neural networks and delivers a rapid, reproducible, and scalable model to investigate long-range functional communication of the nervous system in healthy and disease states.

Bibliometric and visual analysis of single-cell multiomics in neurodegenerative disease arrest studies

Background

Neurodegenerative diseases are progressive disorders that severely diminish the quality of life of patients. However, research on neurodegenerative diseases needs to be refined and deepened. Single-cell polyomics is a technique for obtaining transcriptomic, proteomic, and other information from a single cell. In recent years, the heat of single-cell multiomics as an emerging research tool for brain science has gradually increased. Therefore, the aim of this study was to analyze the current status and trends of studies related to the application of single-cell multiomics in neurodegenerative diseases through bibliometrics.

Result

A total of 596 publications were included in the bibliometric analysis. Between 2015 and 2022, the number of publications increased annually, with the total number of citations increasing significantly, exhibiting the fastest rate of growth between 2019 and 2022. The country/region collaboration map shows that the United States has the most publications and cumulative citations, and that China and the United States have the most collaborations. The institutions that produced the greatest number of articles were Harvard Medical School, Skupin, Alexander, and Wiendl. Among the authors, Heinz had the highest output. Mathys, H accumulated the most citations and was the authoritative author in the field. The journal Nature Communications has published the most literature in this field. A keyword analysis reveals that neurodegenerative diseases and lesions (e.g., Alzheimer's disease, amyloid beta) are the core and foundation of the field. Conversely, single-cell multiomics related research (e.g., single-cell RNA sequencing, bioinformatics) and brain nerve cells (e.g., microglia, astrocytes, neural stem cells) are the hot frontiers of this specialty. Among the references, the article "Single-cell transcriptomic analysis of Alzheimer's disease" is the most frequently cited (1,146 citations), and the article "Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq" was the most cited article in the field.

Conclusion

The objective of this study is to employ bibliometric methods to visualize studies related to single-cell multiomics in neurodegenerative diseases. This will enable us to summarize the current state of research and to reveal key trends and emerging hotspots in the field.

Lead Acetate Exposure and Cerebral Amyloid Accumulation: Mechanistic Evaluations in APP/PS1 Mice

BACKGROUND

The role of environmental factors in Alzheimer's disease (AD) pathogenesis remains elusive. Mounting evidence suggests that acute and past exposure to the environmental toxicant lead (Pb) is associated with longitudinal decline in cognitive function, brain atrophy, and greater brain β -amyloid (A β ) deposition. However, the nature of Pb-induced amyloid deposition and how it contributes to AD development remain unclear.

OBJECTIVES

This study investigates the role of Pb in the pathogenesis of cerebral amyloid angiopathy (CAA) and whether plasminogen activator inhibitor-1 (PAI-1) contributes to this process in the APP/PS1 mouse model.

METHODS

Female APP/PS1 mice at 8 wk of age were administered either 50 mg / kg Pb-acetate (PbAc) (i.e., 27 mg   Pb / kg ) or an equivalent molar concentration of sodium acetate (NaAc) via oral gavage once daily for 8 wk. Amyloid deposition and vascular amyloid were determined by immunostaining. In addition, A β perivascular drainage, vascular binding assay, and microglial endocytosis were examined to determine underlying mechanisms. Furthermore, magnetic resonance imaging demyelination imaging was performed in vivo measure the level of demyelination. Finally, Y-maze and Morris water maze tests were assessed to evaluate the cognitive function of mice.

RESULTS

APP/PS1 mice (an AD mice model) exposed to PbAc demonstrated more vascular amyloid deposition less neocortical myelination, and lower cognitive function, as well as greater vascular binding to A β 40 , higher A β 40 / A β 42 ratios, strikingly lower A β 40 levels in the perivascular drainage, and microglial endocytosis. Importantly, exposure to a specific PAI-1 inhibitor, tiplaxtinin, which previously was reported to lower CAA pathology in mice, resulted in less CAA-related outcomes following PbAc exposure.

DISCUSSION

Our findings suggest that PbAc induced CAA/AD pathogenesis via the PAI-1 signaling in the APP/PS1 mouse model, and the inhibition of PAI-1 could be a potential therapeutic target for PbAc-mediated CAA/AD disorders. https://doi.org/10.1289/EHP14384.

HEXIM1 is correlated with Alzheimer's disease pathology and regulates immediate early gene dynamics in neurons

Impaired memory formation and recall is a distinguishing feature of Alzheimer's disease, and memory requires de novo gene transcription in neurons. Rapid and robust transcription of many genes is facilitated by the formation of a poised basal state, in which RNA polymerase II (RNAP2) has initiated transcription, but is paused just downstream of the gene promoter. Neuronal depolarization releases the paused RNAP2 to complete the synthesis of messenger RNA (mRNA) transcripts. Paused RNAP2 release is controlled by positive transcription elongation factor b (P-TEFb), which is sequestered into a larger inactive complex containing Hexamethylene bisacetamide inducible protein 1 (HEXIM1) under basal conditions. In this work, we find that neuronal expression of HEXIM1 mRNA is highly correlated with human Alzheimer's disease pathologies. Furthermore, P-TEFb regulation by HEXIM1 has a significant impact on the rapid induction of neuronal gene transcription, particularly in response to repeated depolarization. These data indicate that HEXIM1/P-TEFb has an important role in inducible gene transcription in neurons, and for setting and resetting the poised state that allows for the robust activation of genes necessary for synaptic plasticity.

GRAPHICAL ABSTRACT

gsQTL: Associating genetic risk variants with gene sets by exploiting their shared variability

To investigate the functional significance of genetic risk loci identified through genome-wide association studies (GWASs), genetic loci are linked to genes based on their capacity to account for variation in gene expression, resulting in expression quantitative trait loci (eQTL). Following this, gene set analyses are commonly used to gain insights into functionality. However, the efficacy of this approach is hampered by small effect sizes and the burden of multiple testing. We propose an alternative approach: instead of examining the cumulative associations of individual genes within a gene set, we consider the collective variation of the entire gene set. We introduce the concept of gene set QTL (gsQTL), and show it to be more adept at identifying links between genetic risk variants and specific gene sets. Notably, gsQTL experiences less susceptibility to inflation or deflation of significant enrichments compared with conventional methods. Furthermore, we demonstrate the broader applicability of shared variability within gene sets. This is evident in scenarios such as the coordinated regulation of genes by a transcription factor or coordinated differential expression.

The ROSMAP project: aging and neurodegenerative diseases through omic sciences

The Religious Order Study and Memory and Aging Project (ROSMAP) is an initiative that integrates two longitudinal cohort studies, which have been collecting clinicopathological and molecular data since the early 1990s. This extensive dataset includes a wide array of omic data, revealing the complex interactions between molecular levels in neurodegenerative diseases (ND) and aging. Neurodegenerative diseases (ND) are frequently associated with morbidity and cognitive decline in older adults. Omics research, in conjunction with clinical variables, is crucial for advancing our understanding of the diagnosis and treatment of neurodegenerative diseases. This summary reviews the extensive omics research-encompassing genomics, transcriptomics, proteomics, metabolomics, epigenomics, and multiomics-conducted through the ROSMAP study. It highlights the significant advancements in understanding the mechanisms underlying neurodegenerative diseases, with a particular focus on Alzheimer's disease.

Uncovering Plaque-Glia Niches in Human Alzheimer's Disease Brains Using Spatial Transcriptomics

Amyloid-beta (Aβ) plaques and surrounding glial activation are prominent histopathological hallmarks of Alzheimer's Disease (AD). However, it is unclear how Aβ plaques interact with surrounding glial cells in the human brain. Here, we applied spatial transcriptomics (ST) and immunohistochemistry (IHC) for Aβ, GFAP, and IBA1 to acquire data from 258,987 ST spots within 78 postmortem brain sections of 21 individuals. By coupling ST and adjacent-section IHC, we showed that low Aβ spots exhibit transcriptomic profiles indicative of greater neuronal loss than high Aβ spots, and high-glia spots present transcriptomic changes indicative of more significant inflammation and neurodegeneration. Furthermore, we observed that this ST glial response bears signatures of reported mouse gene modules of plaque-induced genes (PIG), oligodendrocyte (OLIG) response, disease-associated microglia (DAM), and disease-associated astrocytes (DAA), as well as different microglia (MG) states identified in human AD brains, indicating that multiple glial cell states arise around plaques and contribute to local immune response. We then validated the observed effects of Aβ on cell apoptosis and plaque-surrounding glia on inflammation and synaptic loss using IHC. In addition, transcriptomic changes of iPSC-derived microglia-like cells upon short-interval Aβ treatment mimic the ST glial response and mirror the reported activated MG states. Our results demonstrate an exacerbation of synaptic and neuronal loss in low-Aβ or high-glia areas, indicating that microglia response to Aβ-oligomers likely initiates glial activation in plaque-glia niches. Our study lays the groundwork for future pathology genomics studies, opening the door for investigating pathological heterogeneity and causal effects in neurodegenerative diseases.