Epigenomic dissection of Alzheimer's disease pinpoints causal variants and reveals epigenome erosion

Decoding Alzheimer's Disease: Single-Cell Sequencing Uncovers Brain Cell Heterogeneity and Pathogenesis

Alzheimer's disease (AD) is a complex neurodegenerative disorder marked by progressive cognitive decline and diverse neuropathological features. Recent advances in single-cell sequencing technologies have provided unprecedented insights into the cellular and molecular heterogeneity of the AD brain. This review systematically summarizes the applications of single-cell transcriptomic and epigenomic approaches in AD research, with a focus on the characterization of cell type- and subtype-specific transcriptomic alterations. This review highlights key discoveries related to selectively vulnerable neuronal and glial subpopulations, as well as transcriptional dysregulation associated with genetic risk loci such as APOE and TREM2. This review also discusses how the integration of single-cell RNA sequencing (scRNA-seq), assays for transposase-accessible chromatin using sequencing (ATAC-seq), and spatial transcriptomics elucidates disease trajectories and cellular communication networks across pathological stages. These insights not only enhance the understanding of the pathogenesis of AD but also pave the way for precision medicine through the identification of novel therapeutic targets and biomarkers.

Revolutionizing Alzheimer's Detection: Immune-Related Gene Biomarkers as Non-Invasive Predictors

Despite recent advancements, the development of an efficient and non-invasive early detection approach for Alzheimer's disease (AD) remains unresolved. The specificity of a diagnostic biomarker is contingent upon its foundation in the molecular basis of the diseases. Immune system dysfunction has a significant role in the genesis and progression of AِِD; thus, it should be included into the formulation of novel treatment and diagnostic strategies. A screening step was conducted through the analysis of a microarray dataset to identify differentially expressed genes (DEGs) and co-expression patterns using weighted gene co-expression network analysis. Subsequently, common genes were discovered and subjected to functional enrichment analysis. Subsequently, during the validation phase, the expression and diagnostic capabilities of candidate genes were evaluated in a group of 50 AD patients. Initially, 269 DEGs were found in the blood of AD patients. Analyzing the co-expression patterns revealed 18 distinct topological modules, with the module exhibiting the highest correlation (blue) selected for further study. A compilation of immune-related genes was extracted from the Immunology Database and Analysis Portal (ImmPort) and cross-referenced with DEGs and genes inside the blue module, as the blue module was found to primarily govern immune response. The anomalous expression of three potential genes-specifically IL17C, TEK, and CCL4-was confirmed in the blood of AD patients by RT-PCR. A biomarker panel consisting of these genes attained an accuracy of 80.2%. The proposed biomarker in this study is based on the immunological response observed in AD and demonstrates high precision in identifying patients.

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.

Drug-targeted Mendelian randomization analysis combined with transcriptome sequencing to explore the molecular mechanisms associated with cognitive impairment

BackgroundCurrent therapies for cognitive impairment, including Alzheimer's disease (AD) and mild cognitive impairment, are limited by a lack of universal treatment and adverse effects associated with polypharmacy. Investigating genetic and molecular mechanisms underlying cognitive decline is critical for the development of targeted therapeutics.ObjectiveTo identify causal genes and potential therapeutic targets for cognitive impairment through integrative genomic analyses.MethodsGenome-wide association study data on cognitive impairment were combined with the expression quantitative trait loci (eQTL) data from the eQTLGen consortium. Mendelian randomization (MR) and colocalization analyses were employed to infer causal relationships. Gene Set Enrichment Analysis and Gene Set Variation Analysis evaluated the pathway and functional differences. Immune cell infiltration patterns and the immunometabolic pathways were assessed, followed by drug target prediction.ResultsMR analysis identified seven gene-eQTL pairs significantly associated with cognitive impairment. SMR colocalization prioritized three key genes: HNMT (histamine metabolism), TNFSF8 (inflammatory signaling), and S1PR5 (sphingolipid signaling). HNMT, TNFSF8, and S1PR5 had 39, 24, and 30 predicted targeted drugs, respectively, including arsenic trioxide, aspirin, and immunomodulators.ConclusionsThis study implicates HNMT, TNFSF8, and S1PR5 as potential therapeutic targets for cognitive impairment. Further validation is required to confirm their clinical relevance.

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.

Mettl3 regulates the pathogenesis of Alzheimer's disease via fine-tuning Lingo2

Alzheimer's disease (AD) is the most common neurodegenerative disease, and diverse factors contribute to its pathogenesis. Previous studies have suggested the dysregulation of m6A modification involves in AD, but the underlying mechanism and targets remain largely unknown. In the present study, we have shown that the levels of Mettl3 and m6A modification are increased in specific brain regions of 5xFAD mice and post-mortem AD patients, respectively. Heterozygous deletion of neuronal Mettl3 (AD::Mettl3+/-) reduced Aβ plaques and inflammation, and improved learning and memory of AD mice, and vice versa for Mettl3 knock in (AD::Mettl3-KI). Mechanistically, we observed that the level of m6A modification of Lingo2 increased in 5xFAD mice and AD patients, which promoted the binding of Ythdf2 and enhanced the degradation of Lingo2 mRNA. The decreased level of Lingo2 promoted the interaction between APP and β-site amyloid precursor protein cleaving enzyme (Bace1), and subsequently enhanced Aβ production in AD mice, which can be inhibited by Mettl3 depletion. Both ectopic Lingo2 and the administration of Mettl3 inhibitor STM2457 significantly alleviated the neuropathology and behavioral deficits of AD mice. In summary, our study has revealed the important function of Mettl3 and m6A in the pathogenesis of AD and provided novel insight for the underlying mechanisms. Our study also suggests that m6A and Lingo2 could be potential therapeutic targets for AD.

Exploring epigenetic modifications as potential biomarkers and therapeutic targets in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder and the most common motor neuron disease. Whole-genome sequencing has identified many novel ALS-associated genes, but genetics alone cannot fully explain the onset of ALS and an effective treatment is still lacking. Moreover, we need more biomarkers for accurate diagnosis and assessment of disease prognosis. Epigenetics, which includes DNA methylation and hydroxymethylation, histone modifications, chromatin remodeling, and non-coding RNAs, influences gene transcription and expression by affecting chromatin accessibility and transcription factor binding without altering genetic information. These processes play a role in the onset and progression of ALS. Epigenetic targets can serve as potential biomarkers and more importantly, the reversibility of epigenetic changes supports their potential role as versatile therapeutic targets in ALS. This review summarized the alterations in different epigenetic modulations in ALS. Additionally, given the close association between aberrant metabolic profiles characterized by hypoxia and high glycolytic metabolism in ALS and epigenetic changes, we also integrate epigenetics with metabolomics. Finally, we discuss the application of therapies based on epigenetic mechanisms in ALS. Our data integration helps to identify potential diagnostic and prognostic biomarkers and support the development of new effective therapies.

Senescent brain cell types in Alzheimer's disease: Pathological mechanisms and therapeutic opportunities

Cellular senescence is a cell state triggered by programmed physiological processes or cellular stress responses. Stress-induced senescent cells often acquire pathogenic traits, including a toxic secretome and resistance to apoptosis. When pathogenic senescent cells form faster than they are cleared by the immune system, they accumulate in tissues throughout the body and contribute to age-related diseases, including neurodegeneration. This review highlights evidence of pathogenic senescent cells in the brain and their role in Alzheimer's disease (AD), the leading cause of dementia in older adults. We also discuss the progress and challenges of senotherapies, pharmacological strategies to clear senescent cells or mitigate their toxic effects, which hold promise as interventions for AD and related dementias (ADRD).

Genetic risk for neurodegenerative conditions is linked to disease-specific microglial pathways

Genome-wide association studies have identified thousands of common variants associated with an increased risk of neurodegenerative disorders. However, the noncoding localization of these variants has made the assignment of target genes for brain cell types challenging. Genomic approaches that infer chromosomal 3D architecture can link noncoding risk variants and distal gene regulatory elements such as enhancers to gene promoters. By using enhancer-to-promoter interactome maps for human microglia, neurons, and oligodendrocytes, we identified cell-type-specific enrichment of genetic heritability for brain disorders through stratified linkage disequilibrium score regression. Our analysis suggests that genetic heritability for multiple neurodegenerative disorders is enriched at microglial chromatin contact sites, while schizophrenia heritability is predominantly enriched at chromatin contact sites in neurons followed by oligodendrocytes. Through Hi-C coupled multimarker analysis of genomic annotation (H-MAGMA), we identified disease risk genes for Alzheimer's disease, Parkinson's disease, multiple sclerosis, amyotrophic lateral sclerosis and schizophrenia. We found that disease-risk genes were overrepresented in microglia compared to other brain cell types across neurodegenerative conditions and within neurons for schizophrenia. Notably, the microglial risk genes and pathways identified were largely specific to each disease. Our findings reinforce microglia as an important, genetically informed cell type for therapeutic interventions in neurodegenerative conditions and highlight potentially targetable disease-relevant pathways.

Single-cell parallel analysis of DNA damage and transcriptome reveals selective genome vulnerability

Maintenance of genome integrity is paramount to molecular programs in multicellular organisms. Throughout the lifespan, various endogenous and environmental factors pose persistent threats to the genome, which can result in DNA damage. Understanding the functional consequences of DNA damage requires investigating their preferred genomic distributions and influences on gene regulatory programs. However, such analysis is hindered by both the complex cell-type compositions within organs and the high background levels due to the stochasticity of damage formation. To address these challenges, we developed Paired-Damage-seq for joint analysis of oxidative and single-stranded DNA damage with gene expression in single cells. We applied this approach to cultured HeLa cells and the mouse brain as a proof of concept. Our results indicated the associations between damage formation and epigenetic changes. The distribution of oxidative DNA damage hotspots exhibits cell-type-specific patterns; this selective genome vulnerability, in turn, can predict cell types and dysregulated molecular programs that contribute to disease risks.

The night's watch: Exploring how sleep protects against neurodegeneration

Sleep loss is often regarded as an early manifestation of neurodegenerative diseases given its common occurrence and link to cognitive dysfunction. However, the precise mechanisms by which sleep disturbances contribute to neurodegeneration are not fully understood, nor is it clear why some individuals are more susceptible to these effects than others. This review addresses critical unanswered questions in the field, including whether sleep disturbances precede or result from neurodegenerative diseases, the functional significance of sleep changes during the preclinical disease phase, and the potential role of sleep homeostasis as an adaptive mechanism enhancing resilience against cognitive decline and neurodegeneration.

All the single cells: Single-cell transcriptomics/epigenomics experimental design and analysis considerations for glial biologists

Single-cell transcriptomics, epigenomics, and other 'omics applied at single-cell resolution can significantly advance hypotheses and understanding of glial biology. Omics technologies are revealing a large and growing number of new glial cell subtypes, defined by their gene expression profile. These subtypes have significant implications for understanding glial cell function, cell-cell communications, and glia-specific changes between homeostasis and conditions such as neurological disease. For many, the training in how to analyze, interpret, and understand these large datasets has been through reading and understanding literature from other fields like biostatistics. Here, we provide a primer for glial biologists on experimental design and analysis of single-cell RNA-seq datasets. Our goal is to further the understanding of why decisions are made about datasets and to enhance biologists' ability to interpret and critique their work and the work of others. We review the steps involved in single-cell analysis with a focus on decision points and particular notes for glia. The goal of this primer is to ensure that single-cell 'omics experiments continue to advance glial biology in a rigorous and replicable way.

Advancements in omics technologies: Molecular mechanisms of acute lung injury and acute respiratory distress syndrome (Review)

Acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) is an inflammatory response arising from lung and systemic injury with diverse causes and associated with high rates of morbidity and mortality. To date, no fully effective pharmacological therapies have been established and the relevant underlying mechanisms warrant elucidation, which may be facilitated by multi‑omics technology. The present review summarizes the application of multi‑omics technology in identifying novel diagnostic markers and therapeutic strategies of ALI/ARDS as well as its pathogenesis.

Deep learning-based cell-specific gene regulatory networks inferred from single-cell multiome data

Gene regulatory networks (GRNs) provide a global representation of how genetic/genomic information is transferred in living systems and are a key component in understanding genome regulation. Single-cell multiome data provide unprecedented opportunities to reconstruct GRNs at fine-grained resolution. However, the inference of GRNs is hindered by insufficient single omic profiles due to the characteristic high loss rate of single-cell sequencing data. In this study, we developed scMultiomeGRN, a deep learning framework to infer transcription factor (TF) regulatory networks via unique integration of single-cell genomic (single-cell RNA sequencing) and epigenomic (single-cell ATAC sequencing) data. We create scMultiomeGRN to elucidate these networks by conceptualizing TF network graph structures. Specifically, we build modality-specific neighbor aggregators and cross-modal attention modules to learn latent representations of TFs from single-cell multi-omics. We demonstrate that scMultiomeGRN outperforms state-of-the-art models on multiple benchmark datasets involved in diseases and health. Via scMultiomeGRN, we identified Alzheimer's disease-relevant regulatory network of SPI1 and RUNX1 for microglia. In summary, scMultiomeGRN offers a deep learning framework to identify cell type-specific gene regulatory network from single-cell multiome data.

Accelerated epigenetic aging in Huntington's disease involves polycomb repressive complex 1

Loss of epigenetic information during physiological aging compromises cellular identity, leading to de-repression of developmental genes. Here, we assessed the epigenomic landscape of vulnerable neurons in two reference mouse models of Huntington neurodegenerative disease (HD), using cell-type-specific multi-omics, including temporal analysis at three disease stages via FANS-CUT&Tag. We show accelerated de-repression of developmental genes in HD striatal neurons, involving histone re-acetylation and depletion of H2AK119 ubiquitination and H3K27 trimethylation marks, which are catalyzed by polycomb repressive complexes 1 and 2 (PRC1 and PRC2), respectively. We further identify a PRC1-dependent subcluster of bivalent developmental transcription factors that is re-activated in HD striatal neurons. This mechanism likely involves progressive paralog switching between PRC1-CBX genes, which promotes the upregulation of normally low-expressed PRC1-CBX2/4/8 isoforms in striatal neurons, alongside the down-regulation of predominant PRC1-CBX isoforms in these cells (e.g., CBX6/7). Collectively, our data provide evidence for PRC1-dependent accelerated epigenetic aging in HD vulnerable neurons.

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.

Massive changes in gene expression and their cause(s) can be a unifying principle in the pathobiology of Alzheimer's disease

Understanding of the biology of Alzheimer's disease (AD) has long been fragmented, with various investigators concentrating on amyloid beta (Aβ) or tau, inflammation, cell death pathways, misfolded proteins, glia, and more. Yet data from multiple authors has repeatedly shown altered expression of myriad genes related to these seemingly disparate phenomena. In 2022, Morgan et al. organized the massive data on changes in AD in a meticulous survey of the literature and related these changes to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Their data showed that 91% of the known KEGG pathways are involved in AD and that many of these pathways are represented by the known cellular/molecular phenomena of AD. Such data then raise the fundamental question: What mechanism(s) may be responsible for such widespread changes in gene expression? We review evidence for a unifying model based on sequestrations in stress granules and alteration of nucleocytoplasmic transport in AD. HIGHLIGHTS: In Alzheimer's disease (AD), critical changes take place in neurons before the appearance of plaques or tangles. Addressing these early changes provides a path to early detection and effective intervention in AD.

Functional insight into East Asian-specific genetic risk loci for Alzheimer's disease

INTRODUCTION

The functional study of genetic risk factors for Alzheimer's disease (AD) provides insights into the underlying mechanisms and identification of potential therapeutic targets. Investigating AD-associated genetic loci identified in East Asian populations using single-nucleus RNA-sequencing data may identify novel functional genetic contributors.

METHODS

Cell type-specific expression quantitative trait loci (eQTL) and peak-to-gene links were used to identify functional genes associated with 26 genetic loci from seven genome-wide association studies (GWAS) for AD in East Asians.

RESULTS

KCNJ6 and MAPK1IP1L were identified as significant eQTLs with AD risk loci. AD risk loci were in peaks related to four genes, with CLIC4 being connected across different cell types. Genes identified in European and East Asian GWAS interacted within networks and were enriched in AD pathology pathways in astrocytes.

DISCUSSION

Our findings suggest KCNJ6 and CLIC4 as novel AD-associated functional genes, providing insight into the genetic architecture of AD in East Asians.

HIGHLIGHTS

Integrated functional analysis of Alzheimer's disease (AD) loci in seven East Asian genome-wide association studies (GWAS) was performed. Cell type-specific expression quantitative trait loci (eQTLs) and assay for transposase-accessible chromatin peaks were used to identify AD functional genes. An AD risk variant was linked to KCNJ6 through an oligodendrocyte progenitor cell-specific eQTL. An AD risk variant maps to open chromatin, linked to CLIC4 across six cell types. Astrocyte differentially expressed genes by AD pathology are enriched in East Asian and European GWAS genes.

Alzheimer's disease: insights into pathology, molecular mechanisms, and therapy

Alzheimer's disease (AD), the leading cause of dementia, is characterized by the accumulation of amyloid plaques and neurofibrillary tangles in the brain. This condition casts a significant shadow on global health due to its complex and multifactorial nature. In addition to genetic predispositions, the development of AD is influenced by a myriad of risk factors, including aging, systemic inflammation, chronic health conditions, lifestyle, and environmental exposures. Recent advancements in understanding the complex pathophysiology of AD are paving the way for enhanced diagnostic techniques, improved risk assessment, and potentially effective prevention strategies. These discoveries are crucial in the quest to unravel the complexities of AD, offering a beacon of hope for improved management and treatment options for the millions affected by this debilitating disease.

Chromatin accessibility provides a window into the genetic etiology of human brain disease

Neuropsychiatric and neurodegenerative diseases have a significant genetic component. Risk variants often affect the noncoding genome, altering cis-regulatory elements (CREs) and chromatin structure, ultimately impacting gene expression. Chromatin accessibility profiling methods, especially assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq), have been used to pinpoint disease-associated SNPs and link them to affected genes and cell types in the brain. The integration of single-cell technologies with genome-wide association studies (GWAS) and transcriptomic data has further advanced our understanding of cell-specific chromatin dynamics. This review discusses recent findings regarding the role played by chromatin accessibility in brain disease, highlighting the need for high-quality data and rigorous computational tools. Future directions include spatial chromatin studies and CRISPR-based functional validation to bridge genetic discovery and clinical applications, paving the way for targeted gene-regulatory therapies.

The impact of genetic variability on Alzheimer's therapies: obstacles for pharmacogenetic progress

INTRODUCTION

Genetic load influences the therapeutic response to conventional drugs in Alzheimer's disease (AD). Pharmacogenetics (PGx) is the best option to reduce drug-drug interactions and adverse drug reactions in patients undergoing polypharmacy regimens. However, there are important limitations that make it difficult to incorporate pharmacogenetics into routine clinical practice.

AREAS COVERED

This article analyzes the pharmacogenetic apparatus made up of pathogenic, mechanistic, metabolic, transporter, and pleiotropic genes responsible for the efficacy and safety of pharmacological treatment, the impact of genetic load on the outcome of multifactorial treatments, and practical aspects for the effective use of PGx.

EXPERT OPINION

Over 120 genes are closely associated with AD. There is an accumulation of cerebrovascular (CVn) and neurodegenerative (ADn) genes in AD. APOE-4 carriers accumulate more deleterious genetic load related to other CVn and ADn genes, develop the disease earlier, and are at a biological disadvantage compared to APOE-4 non-carriers. CYP2D6-PMs and APOE-4 carriers are the worst responders to anti-dementia drugs. Some limitations hinder the implementation of PGx in clinical practice, including lack of pharmacogenetic information for many drugs, low number of genes in PGx screening protocols, and educational deficiencies in the medical community regarding PGx and genomic medicine.

Monitoring of single-nucleus chromatin landscape of ischemic stroke in mouse cerebral cortex across time

Ischemic stroke constitutes a multifaceted neurological affliction that spans various cellular types. Lack of dynamic chromatin accessibility data after stroke is one of the obstacles to understanding this process. To gain insights into the variations in transcriptional regulation among various cell types subsequent to a stroke, we employed single-nucleus ATAC-seq to curate a chromatin accessibility compendium from the cerebral cortex of mice subjected to middle cerebral artery occlusion/reperfusion (MCAO/R). Tissue samples were collected at various time points including 0, 6, 12, 24 hours, and 7, 14 days post-reperfusion, in addition to Sham control group. We obtained 99,271 high-quality nuclei across nine cell types, thereby establishing the single-nucleus chromatin accessibility atlas. This atlas provides data for interpreting the regulatory mechanisms that pervade the continuum of ischemic stroke. The data presented herein constitutes a valuable resource for the comprehension of regulatory interplays within the pathology-afflicted cerebrum.

GoFCards: an integrated database and analytic platform for gain of function variants in humans

Gain-of-function (GOF) variants, which introduce new or amplify protein functions, are essential for understanding disease mechanisms. Despite advances in genomics and functional research, identifying and analyzing pathogenic GOF variants remains challenging owing to fragmented data and database limitations, underscoring the difficulty in accessing critical genetic information. To address this challenge, we manually reviewed the literature, pinpointing 3089 single-nucleotide variants and 72 insertions and deletions in 579 genes associated with 1299 diseases from 2069 studies, and integrated these with the 3.5 million predicted GOF variants. Our approach is complemented by a proprietary scoring system that prioritizes GOF variants on the basis of the evidence supporting their GOF effects and provides predictive scores for variants that lack existing documentation. We then developed a database named GoFCards for general geneticists and clinicians to easily obtain GOF variants in humans (http://www.genemed.tech/gofcards). This database also contains data from >150 sources and offers comprehensive variant-level and gene-level annotations, with the aim of providing users with convenient access to detailed and relevant genetic information. Furthermore, GoFCards empowers users with limited bioinformatic skills to analyze and annotate genetic data, and prioritize GOF variants. GoFCards offers an efficient platform for interpreting GOF variants and thereby advancing genetic research.

GWAS highlights the neuronal contribution to multiple sclerosis susceptibility

Multiple Sclerosis (MS) is a chronic inflammatory and neurodegenerative disease affecting the brain and spinal cord. Genetic studies have identified many risk loci, that were thought to primarily impact immune cells and microglia. Here, we performed a multi-ancestry genome-wide association study with 20,831 MS and 729,220 control participants, identifying 236 susceptibility variants outside the Major Histocompatibility Complex, including four novel loci. We derived a polygenic score for MS and, optimized for European ancestry, it is informative for African-American and Latino participants. Integrating single-cell data from blood and brain tissue, we identified 76 genes affected by MS risk variants. Notably, while T cells showed the strongest enrichment, inhibitory neurons emerged as a key cell type. The expression of IL7 and STAT3 are affected only in inhibitory neurons, highlighting the importance of neuronal and glial dysfunction in MS susceptibility.

Tau mediates the reshaping of the transcriptional landscape toward intermediate Alzheimer's disease stages

Introduction

Recent research revealed that Tau plays critical roles in various neuronal functions. We previously demonstrated that destabilization and nuclear delocalization of Tau alter the expression of glutamatergic genes, mediating early neuronal damage.

Methods

In this study, we discovered that changes in Tau availability are linked to global alterations in gene expression that affect multiple neuronal pathways. Comparison with the human temporal region showed that the Tau-dependent modulation of gene expression closely resembles the intermediate stages of Alzheimer's disease (AD) that precede the definitive pathological condition.

Results

Furthermore, we identified the chromatin remodeling pathway as being significantly affected by Tau in both our cellular model and AD brains, with reductions in heterochromatin markers. Our findings indicate that Tau is able to globally affect the neuronal transcriptome and that its subcellular unbalance changes gene expression in the intermediate stages of AD development. In addition, we found that the chromatin architecture is affected by Tau during the progression of AD.

Discussion

These results provide new insights into the molecular mechanisms underlying early stages of AD development and highlight the central role of Tau and the contribution of nuclear Tau in this process.

Epigenetics in Neurodegenerative Diseases

Healthy brain functioning requires a continuous fine-tuning of gene expression, involving changes in the epigenetic landscape and 3D chromatin organization. Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and frontotemporal dementia (FTD) are three multifactorial neurodegenerative diseases (NDDs) that are partially explained by genetics (gene mutations and genetic risk factors) and influenced by non-genetic factors (i.e., aging, lifestyle, and environmental conditions). Examining comprehensive studies of global and locus-specific (epi)genomic and transcriptomic alterations in human and mouse brain samples at the cell-type resolution has uncovered important phenomena associated with AD. First, DNA methylation and histone marks at promoters contribute to transcriptional dysregulation of genes that are directly implicated in AD pathogenesis (i.e., APP), neuroplasticity and cognition (i.e., PSD95), and microglial activation (i.e., TREM2). Second, the presence of AD genetic risk variants in cell-type-specific distal enhancers (i.e., BIN1 in microglia) alters transcription, presumably by disrupting associated enhancer-promoter interactions and chromatin looping. Third, epigenomic erosion is associated with widespread transcriptional disruption and cell identity loss. And fourth, aging, high cholesterol, air pollution, and pesticides have emerged as potential drivers of AD by inducing locus-specific and global epigenetic modifications that impact key AD-related pathways. Epigenetic studies in ALS/FTD also provide evidence that genetic and non-genetic factors alter gene expression profiles in neurons and astrocytes through aberrant epigenetic mechanisms. We additionally overview the recent development of potential new therapeutic strategies involving (epi)genetic editing and the use of small chromatin-modifying molecules (epidrugs).

Scrutinizing neurodegenerative diseases: decoding the complex genetic architectures through a multi-omics lens

Neurodegenerative diseases present complex genetic architectures, reflecting a continuum from monogenic to oligogenic and polygenic models. Recent advances in multi-omics data, coupled with systems genetics, have significantly refined our understanding of how these data impact neurodegenerative disease mechanisms. To contextualize these genetic discoveries, we provide a comprehensive critical overview of genetic architecture concepts, from Mendelian inheritance to the latest insights from oligogenic and omnigenic models. We explore the roles of common and rare genetic variants, gene-gene and gene-environment interactions, and epigenetic influences in shaping disease phenotypes. Additionally, we emphasize the importance of multi-omics layers including genomic, transcriptomic, proteomic, epigenetic, and metabolomic data in elucidating the molecular mechanisms underlying neurodegeneration. Special attention is given to missing heritability and the contribution of rare variants, particularly in the context of pleiotropy and network pleiotropy. We examine the application of single-cell omics technologies, transcriptome-wide association studies, and epigenome-wide association studies as key approaches for dissecting disease mechanisms at tissue- and cell-type levels. Our review introduces the OmicPeak Disease Trajectory Model, a conceptual framework for understanding the genetic architecture of neurodegenerative disease progression, which integrates multi-omics data across biological layers and time points. This review highlights the critical importance of adopting a systems genetics approach to unravel the complex genetic architecture of neurodegenerative diseases. Finally, this emerging holistic understanding of multi-omics data and the exploration of the intricate genetic landscape aim to provide a foundation for establishing more refined genetic architectures of these diseases, enhancing diagnostic precision, predicting disease progression, elucidating pathogenic mechanisms, and refining therapeutic strategies for neurodegenerative conditions.

Genetic Architecture of Postpartum Psychosis: From Common to Rare Genetic Variation

Postpartum psychosis is a severe psychiatric condition marked by the abrupt onset of psychosis, mania, or psychotic depression following childbirth. Despite evidence for a strong genetic basis, the roles of common and rare genetic variation remain poorly understood. Leveraging data from Swedish national registers and genomic data from the All of Us Research Program, we estimated family-based heritability at 55% and WGS-based heritability at 37%, with an overrepresentation on the X chromosome. Rare coding variant analysis identified DNMT1 and HMGCR as potential risk genes (q < 0.1). Analysis of 240,009 samples from All of Us demonstrated significant associations between these genes and multiple psychiatric disorders, supporting their biological relevance. Additionally, 17% of bipolar disorder, 21% of schizophrenia, and 16-25% of multiple autoimmune disorder risk genes overlapped with postpartum psychosis. These findings reveal unique genetic contributions and shared pathways, providing a foundation for understanding pathophysiology and advancing therapeutic strategies.

GWAS highlights the neuronal contribution to multiple sclerosis susceptibility

Multiple Sclerosis (MS) is a chronic inflammatory and neurodegenerative disease affecting the brain and spinal cord. Genetic studies have identified many risk loci, that were thought to primarily impact immune cells and microglia. Here, we performed a multi-ancestry genome-wide association study with 20,831 MS and 729,220 control participants, identifying 236 susceptibility variants outside the Major Histocompatibility Complex, including four novel loci. We derived a polygenic score for MS and, optimized for European ancestry, it is informative for African-American and Latino participants. Integrating single-cell data from blood and brain tissue, we identified 76 genes affected by MS risk variants. Notably, while T cells showed the strongest enrichment, inhibitory neurons emerged as a key cell type, highlighting the importance of neuronal and glial dysfunction in MS susceptibility.

Integrated multimodal cell atlas of Alzheimer's disease

Alzheimer's disease (AD) is the leading cause of dementia in older adults. Although AD progression is characterized by stereotyped accumulation of proteinopathies, the affected cellular populations remain understudied. Here we use multiomics, spatial genomics and reference atlases from the BRAIN Initiative to study middle temporal gyrus cell types in 84 donors with varying AD pathologies. This cohort includes 33 male donors and 51 female donors, with an average age at time of death of 88 years. We used quantitative neuropathology to place donors along a disease pseudoprogression score. Pseudoprogression analysis revealed two disease phases: an early phase with a slow increase in pathology, presence of inflammatory microglia, reactive astrocytes, loss of somatostatin+ inhibitory neurons, and a remyelination response by oligodendrocyte precursor cells; and a later phase with exponential increase in pathology, loss of excitatory neurons and Pvalb+ and Vip+ inhibitory neuron subtypes. These findings were replicated in other major AD studies.

The role of astrocytes in Alzheimer's disease: a bibliometric analysis

Background

Alzheimer's disease (AD) is a neurodegenerative disorder marked by cognitive decline and memory loss. Recent research underscores the crucial role of astrocytes in AD. This study reviews research trends and contributions on astrocytes in AD from 2000 to 2024, shedding light on the evolving research landscape.

Methods

We conducted a bibliometric analysis using data from the Web of Science Core Collection, covering publications from January 1, 2000, to July 6, 2024, on "Alzheimer's disease" and "astrocytes." We identified 5,252 relevant English articles and reviews. For data visualization and analysis, we used VOSviewer, CiteSpace, and the R package "bibliometrix," examining collaboration networks, co-citation networks, keyword co-occurrence, and thematic evolution.

Results

Between 2000 and 2024, 5,252 publications were identified, including 4,125 original research articles and 1,127 review articles. Publications increased significantly after 2016. The United States had the most contributions (1,468), followed by China (836). Major institutions were the University of California system (517) and Harvard University (402). The Journal of Alzheimer's Disease published the most articles (215). Verkhratsky A was the top author with 51 papers and 1,585 co-citations.

Conclusion

Our extensive bibliometric analysis indicates a significant increase in research on astrocytes in AD over the past 20 years. This study emphasizes the growing acknowledgment of astrocytes' crucial role in AD pathogenesis and points to future research on their mechanisms and therapeutic potential.

Therapeutic Options in Alzheimer's Disease: From Classic Acetylcholinesterase Inhibitors to Multi-Target Drugs with Pleiotropic Activity

Alzheimer's disease (AD) is a complex/multifactorial brain disorder involving hundreds of defective genes, epigenetic aberrations, cerebrovascular alterations, and environmental risk factors. The onset of the neurodegenerative process is triggered decades before the first symptoms appear, probably due to a combination of genomic and epigenetic phenomena. Therefore, the primary objective of any effective treatment is to intercept the disease process in its presymptomatic phases. Since the approval of acetylcholinesterase inhibitors (Tacrine, Donepezil, Rivastigmine, Galantamine) and Memantine, between 1993 and 2003, no new drug was approved by the FDA until the advent of immunotherapy with Aducanumab in 2021 and Lecanemab in 2023. Over the past decade, more than 10,000 new compounds with potential action on some pathogenic components of AD have been tested. The limitations of these anti-AD treatments have stimulated the search for multi-target (MT) drugs. In recent years, more than 1000 drugs with potential MT function have been studied in AD models. MT drugs aim to address the complex and multifactorial nature of the disease. This approach has the potential to offer more comprehensive benefits than single-target therapies, which may be limited in their effectiveness due to the intricate pathology of AD. A strategy still unexplored is the combination of epigenetic drugs with MT agents. Another option could be biotechnological products with pleiotropic action, among which nosustrophine-like compounds could represent an attractive, although not definitive, example.

CNV-Profile Regression: A New Approach for Copy Number Variant Association Analysis in Whole Genome Sequencing Data

Copy number variants (CNVs) are DNA gains or losses involving >50 base pairs. Assessing CNV effects on disease risk requires consideration of several factors. First, there are no natural definitions for CNV loci. Second, CNV effects can depend on dosage and length. Third, CNV effects can be more accurately estimated when all CNV events in a genomic region are analyzed together to assess their joint effects. We propose a new framework for association analysis that directly models an individual's entire CNV profile within a genomic region. This framework represents an individual's CNVs using a CNV profile curve to capture variations in CNV length and dosage and to bypass the need to predefine CNV loci. CNV effects are estimated at each genome position, making the results comparable across different studies. To jointly estimate the effects of all CNVs, we use a Lasso penalty to select CNVs associated with the trait and integrate a weighted L2-fusion penalty to encourage similar effects of adjacent CNVs when supported by the data. Simulations show that the proposed model can more effectively identify causal CNVs while maintaining false positive rates comparable to baseline methods and yield more precise effect-size estimates across different settings. When applied to CNV derived from whole genome sequencing data of the Alzheimer's Disease Sequencing Project, the proposed methods identify additional CNVs associated with Alzheimer's Disease (AD). These identified CNVs overlap with several known AD-risk genes and are significantly enriched by biological processes related to neuron structures and functions crucial in AD development.

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.

Therapeutic targeting of senescent cells in the CNS

Senescent cells accumulate throughout the body with advanced age, diseases and chronic conditions. They negatively impact health and function of multiple systems, including the central nervous system (CNS). Therapies that target senescent cells, broadly referred to as senotherapeutics, recently emerged as potentially important treatment strategies for the CNS. Promising therapeutic approaches involve clearing senescent cells by disarming their pro-survival pathways with 'senolytics'; or dampening their toxic senescence-associated secretory phenotype (SASP) using 'senomorphics'. Following the pioneering discovery of first-generation senolytics dasatinib and quercetin, dozens of additional therapies have been identified, and several promising targets are under investigation. Although potentially transformative, senotherapies are still in early stages and require thorough testing to ensure reliable target engagement, specificity, safety and efficacy. The limited brain penetrance and potential toxic side effects of CNS-acting senotherapeutics pose challenges for drug development and translation to the clinic. This Review assesses the potential impact of senotherapeutics for neurological conditions by summarizing preclinical evidence, innovative methods for target and biomarker identification, academic and industry drug development pipelines and progress in clinical trials.

Cellular and pathological functions of tau

Tau protein is involved in various cellular processes, including having a canonical role in binding and stabilization of microtubules in neurons. Tauopathies are neurodegenerative diseases marked by the abnormal accumulation of tau protein aggregates in neurons, as seen, for example, in conditions such as frontotemporal dementia and Alzheimer disease. Mutations in tau coding regions or that disrupt tau mRNA splicing, tau post-translational modifications and cellular stress factors (such as oxidative stress and inflammation) increase the tendency of tau to aggregate and interfere with its clearance. Pathological tau is strongly implicated in the progression of neurodegenerative diseases, and the propagation of tau aggregates is associated with disease severity. Recent technological advancements, including cryo-electron microscopy and disease models derived from human induced pluripotent stem cells, have increased our understanding of tau-related pathology in neurodegenerative conditions. Substantial progress has been made in deciphering tau aggregate structures and the molecular mechanisms that underlie protein aggregation and toxicity. In this Review, we discuss recent insights into the diverse cellular functions of tau and the pathology of tau inclusions and explore the potential for therapeutic interventions.

Genetic and clinical correlates of two neuroanatomical AI dimensions in the Alzheimer's disease continuum

Alzheimer's disease (AD) is associated with heterogeneous atrophy patterns. We employed a semi-supervised representation learning technique known as Surreal-GAN, through which we identified two latent dimensional representations of brain atrophy in symptomatic mild cognitive impairment (MCI) and AD patients: the "diffuse-AD" (R1) dimension shows widespread brain atrophy, and the "MTL-AD" (R2) dimension displays focal medial temporal lobe (MTL) atrophy. Critically, only R2 was associated with widely known sporadic AD genetic risk factors (e.g., APOE ε4) in MCI and AD patients at baseline. We then independently detected the presence of the two dimensions in the early stages by deploying the trained model in the general population and two cognitively unimpaired cohorts of asymptomatic participants. In the general population, genome-wide association studies found 77 genes unrelated to APOE differentially associated with R1 and R2. Functional analyses revealed that these genes were overrepresented in differentially expressed gene sets in organs beyond the brain (R1 and R2), including the heart (R1) and the pituitary gland, muscle, and kidney (R2). These genes were enriched in biological pathways implicated in dendritic cells (R2), macrophage functions (R1), and cancer (R1 and R2). Several of them were "druggable genes" for cancer (R1), inflammation (R1), cardiovascular diseases (R1), and diseases of the nervous system (R2). The longitudinal progression showed that APOE ε4, amyloid, and tau were associated with R2 at early asymptomatic stages, but this longitudinal association occurs only at late symptomatic stages in R1. Our findings deepen our understanding of the multifaceted pathogenesis of AD beyond the brain. In early asymptomatic stages, the two dimensions are associated with diverse pathological mechanisms, including cardiovascular diseases, inflammation, and hormonal dysfunction-driven by genes different from APOE-which may collectively contribute to the early pathogenesis of AD. All results are publicly available at https://labs-laboratory.com/medicine/ .

Cross-disorder and disease-specific pathways in dementia revealed by single-cell genomics

The development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNA-seq and ATAC-seq in Alzheimer's disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP), analyzing 41 participants and ∼1 million cells (RNA + ATAC) from three brain regions varying in vulnerability and pathological burden. We identify 32 shared, disease-associated cell types and 14 that are disease specific. Disease-specific cell states represent glial-immune mechanisms and selective neuronal vulnerability impacting layer 5 intratelencephalic neurons in AD, layer 2/3 intratelencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We identify disease-associated gene regulatory networks and cells impacted by causal genetic risk, which differ by disorder. These data illustrate the heterogeneous spectrum of glial and neuronal compositional and gene expression alterations in different dementias and identify therapeutic targets by revealing shared and disease-specific cell states.

Cognitive resilience to Alzheimer's disease characterized by cell-type abundance

INTRODUCTION

The molecular basis of cognitive resilience (CR) among pathologically confirmed Alzheimer's disease (AD) cases is not well understood.

METHODS

Abundance of 13 cell types and neuronal subtypes in brain bulk RNA-seq data from the anterior caudate, dorsolateral prefrontal cortex (DLPFC), and posterior cingulate cortex (PCC) obtained from 434 AD cases, 318 cognitively resilient AD cases, and 188 controls in the Religious Orders Study and Rush Memory and Aging Project was estimated by deconvolution.

RESULTS

PVALB+ neuron abundance was negatively associated with cognitive status and tau pathology in the DLPFC and PCC (Padj < 0.001) and the most reduced neuronal subtype in AD cases compared to controls in DLPFC (Padj = 8.4 × 10-7) and PCC (Padj = 0.0015). We identified genome-wide significant association of neuron abundance with TMEM106B single nucleotide polymorphism rs13237518 in PCC (p = 6.08 × 10-12). rs13237518 was also associated with amyloid beta (p = 0.0085) and tangles (p = 0.0073).

DISCUSSION

High abundance of PVALB+ neurons may be a marker of CR. TMEM106B variants may influence CR independent of AD pathology.

HIGHLIGHTS

Neuron retention and a lack of astrocytosis are highly predictive of Alzheimer's disease (AD) resilience. PVALB+ GABAergic and RORB+ glutamatergic neurons are associated with cognitive status. A TMEM106B single nucleotide polymorphism is related to lower AD risk, higher neuron count, and increased AD pathology.

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

Mapping enhancers and target genes in disease-related cell types has provided critical insights into the functional mechanisms of genetic variants identified by genome-wide association studies (GWAS). However, most existing analyses rely on bulk data or cultured cell lines, which may fail to identify cell-type-specific enhancers and target genes. Recently, single-cell multimodal data measuring both gene expression and chromatin accessibility within the same cells have enabled the inference of enhancer-gene pairs in a cell-type-specific and context-specific manner. However, this task is challenged by the data's high sparsity, sequencing depth variation, and the computational burden of analyzing a large number of enhancer-gene pairs. To address these challenges, we propose 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 systematic analyses of blood and brain data, scMultiMap shows appropriate type I error control, high statistical power with greater reproducibility across independent datasets and stronger consistency with orthogonal data modalities. Meanwhile, its computational cost is less than 1% of existing methods. When applied to single-cell multimodal data from postmortem brain samples from Alzheimer's disease (AD) patients and controls, scMultiMap gave the highest heritability enrichment in microglia and revealed new insights into the regulatory mechanisms of AD GWAS variants in microglia.

Beyond the usual suspects: multi-factorial computational models in the search for neurodegenerative disease mechanisms

From Alzheimer's disease to amyotrophic lateral sclerosis, the molecular cascades underlying neurodegenerative disorders remain poorly understood. The clinical view of neurodegeneration is confounded by symptomatic heterogeneity and mixed pathology in almost every patient. While the underlying physiological alterations originate, proliferate, and propagate potentially decades before symptomatic onset, the complexity and inaccessibility of the living brain limit direct observation over a patient's lifespan. Consequently, there is a critical need for robust computational methods to support the search for causal mechanisms of neurodegeneration by distinguishing pathogenic processes from consequential alterations, and inter-individual variability from intra-individual progression. Recently, promising advances have been made by data-driven spatiotemporal modeling of the brain, based on in vivo neuroimaging and biospecimen markers. These methods include disease progression models comparing the temporal evolution of various biomarkers, causal models linking interacting biological processes, network propagation models reproducing the spatial spreading of pathology, and biophysical models spanning cellular- to network-scale phenomena. In this review, we discuss various computational approaches for integrating cross-sectional, longitudinal, and multi-modal data, primarily from large observational neuroimaging studies, to understand (i) the temporal ordering of physiological alterations, i(i) their spatial relationships to the brain's molecular and cellular architecture, (iii) mechanistic interactions between biological processes, and (iv) the macroscopic effects of microscopic factors. We consider the extents to which computational models can evaluate mechanistic hypotheses, explore applications such as improving treatment selection, and discuss how model-informed insights can lay the groundwork for a pathobiological redefinition of neurodegenerative disorders.

Integrating amyloid and tau imaging with proteomics and genomics in Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disease and is characterized by the aggregation of β-amyloid (Aβ) and tau in the brain. Breakthroughs in disease-modifying treatments targeting Aβ bring new hope for the management of AD. But to effectively modify and someday even prevent AD, a better understanding is needed of the biological mechanisms that underlie and link Aβ and tau in AD. Developments of high-throughput omics, including genomics, proteomics, and transcriptomics, together with molecular imaging of Aβ and tau with positron emission tomography (PET), allow us to discover and understand the biological pathways that regulate the aggregation and spread of Aβ and tau in living humans. The field of integrated omics and PET studies of Aβ and tau in AD is growing rapidly. We here provide an update of this field, both in terms of biological insights and in terms of future clinical implications of integrated omics-molecular imaging studies.

Single-nucleus multi-omics identifies shared and distinct pathways in Pick's and Alzheimer's disease

The study of neurodegenerative diseases, particularly tauopathies like Pick's disease (PiD) and Alzheimer's disease (AD), offers insights into the underlying regulatory mechanisms. By investigating epigenomic variations in these conditions, we identified critical regulatory changes driving disease progression, revealing potential therapeutic targets. Our comparative analyses uncovered disease-enriched non-coding regions and genome-wide transcription factor (TF) binding differences, linking them to target genes. Notably, we identified a distal human-gained enhancer (HGE) associated with E3 ubiquitin ligase (UBE3A), highlighting disease-specific regulatory alterations. Additionally, fine-mapping of AD risk genes uncovered loci enriched in microglial enhancers and accessible in other cell types. Shared and distinct TF binding patterns were observed in neurons and glial cells across PiD and AD. We validated our findings using CRISPR to excise a predicted enhancer region in UBE3A and developed an interactive database (http://swaruplab.bio.uci.edu/scROAD) to visualize predicted single-cell TF occupancy and regulatory networks.

Progress in multifactorial single-cell chromatin profiling methods

Chromatin states play a key role in shaping overall cellular states and fates. Building a complete picture of the functional state of chromatin in cells requires the co-detection of several distinct biochemical aspects. These span DNA methylation, chromatin accessibility, chromosomal conformation, histone posttranslational modifications, and more. While this certainly presents a challenging task, over the past few years many new and creative methods have been developed that now enable co-assay of these different aspects of chromatin at single cell resolution. This field is entering an exciting phase, where a confluence of technological improvements, decreased sequencing costs, and computational innovation are presenting new opportunities to dissect the diversity of chromatin states present in tissues, and how these states may influence gene regulation. In this review, I discuss the spectrum of current experimental approaches for multifactorial chromatin profiling, highlight some of the experimental and analytical challenges, as well as some areas for further innovation.

A human fetal cerebellar map of the late second trimester reveals developmental molecular characteristics and abnormality in trisomy 21

Our understanding of human fetal cerebellum development during the late second trimester, a critical period for the generation of astrocytes, oligodendrocytes, and unipolar brush cells (UBCs), remains limited. Here, we performed single-cell RNA sequencing (scRNA-seq) in human fetal cerebellum samples from gestational weeks (GWs) 18-25. We find that proliferating UBC progenitors distribute in the subventricular zone of the rhombic lip (RLSVZ) near white matter (WM), forming a layer structure. We also delineate two trajectories from astrogenic radial glia (ARGs) to Bergmann glial progenitors (BGPs) and recognize oligodendrogenic radial glia (ORGs) as one source of primitive oligodendrocyte progenitor cells (PriOPCs). Additionally, our scRNA-seq analysis of the trisomy 21 fetal cerebellum at this stage reveals abnormal upregulated genes in pathways such as the cell adhesion pathway and focal adhesion pathway, which potentially promote neuronal differentiation. Overall, our research provides valuable insights into normal and abnormal development of the human fetal cerebellum.

Integrative proteomics identifies a conserved Aβ amyloid responsome, novel plaque proteins, and pathology modifiers in Alzheimer's disease

Alzheimer's disease (AD) is a complex neurodegenerative disorder that develops over decades. AD brain proteomics reveals vast alterations in protein levels and numerous altered biologic pathways. Here, we compare AD brain proteome and network changes with the brain proteomes of amyloid β (Aβ)-depositing mice to identify conserved and divergent protein networks with the conserved networks identifying an Aβ amyloid responsome. Proteins in the most conserved network (M42) accumulate in plaques, cerebrovascular amyloid (CAA), and/or dystrophic neuronal processes, and overexpression of two M42 proteins, midkine (Mdk) and pleiotrophin (PTN), increases the accumulation of Aβ in plaques and CAA. M42 proteins bind amyloid fibrils in vitro, and MDK and PTN co-accumulate with cardiac transthyretin amyloid. M42 proteins appear intimately linked to amyloid deposition and can regulate amyloid deposition, suggesting that they are pathology modifiers and thus putative therapeutic targets. We posit that amyloid-scaffolded accumulation of numerous M42+ proteins is a central mechanism mediating downstream pathophysiology in AD.

Single-Cell Patch-Clamp/Proteomics of Human Alzheimer's Disease iPSC-Derived Excitatory Neurons Versus Isogenic Wild-Type Controls Suggests Novel Causation and Therapeutic Targets

Standard single-cell (sc) proteomics of disease states inferred from multicellular organs or organoids cannot currently be related to single-cell physiology. Here, a scPatch-Clamp/Proteomics platform is developed on single neurons generated from hiPSCs bearing an Alzheimer's disease (AD) genetic mutation and compares them to isogenic wild-type controls. This approach provides both current and voltage electrophysiological data plus detailed proteomics information on single-cells. With this new method, the authors are able to observe hyperelectrical activity in the AD hiPSC-neurons, similar to that observed in the human AD brain, and correlate it to ≈1400 proteins detected at the single neuron level. Using linear regression and mediation analyses to explore the relationship between the abundance of individual proteins and the neuron's mutational and electrophysiological status, this approach yields new information on therapeutic targets in excitatory neurons not attainable by traditional methods. This combined patch-proteomics technique creates a new proteogenetic-therapeutic strategy to correlate genotypic alterations to physiology with protein expression in single-cells.

Single-nucleus multiomics reveals the disrupted regulatory programs in three brain regions of sporadic early-onset Alzheimer's disease

Sporadic early-onset Alzheimer's disease (sEOAD) represents a significant but less-studied subtype of Alzheimer's disease (AD). Here, we generated a single-nucleus multiome atlas derived from the postmortem prefrontal cortex, entorhinal cortex, and hippocampus of nine individuals with or without sEOAD. Comprehensive analyses were conducted to delineate cell type-specific transcriptomic changes and linked candidate cis-regulatory elements (cCREs) across brain regions. We prioritized seven conservative transcription factors in glial cells in multiple brain regions, including RFX4 in astrocytes and IKZF1 in microglia, which are implicated in regulating sEOAD-associated genes. Moreover, we identified the top 25 altered intercellular signaling between glial cells and neurons, highlighting their regulatory potential on gene expression in receiver cells. We reported 38 cCREs linked to sEOAD-associated genes overlapped with late-onset AD risk loci, and sEOAD cCREs enriched in neuropsychiatric disorder risk loci. This atlas helps dissect transcriptional and chromatin dynamics in sEOAD, providing a key resource for AD research.

Regression convolutional neural network models implicate peripheral immune regulatory variants in the predisposition to Alzheimer's disease

Alzheimer's disease (AD) involves aggregation of amyloid β and tau, neuron loss, cognitive decline, and neuroinflammatory responses. Both resident microglia and peripheral immune cells have been associated with the immune component of AD. However, the relative contribution of resident and peripheral immune cell types to AD predisposition has not been thoroughly explored due to their similarity in gene expression and function. To study the effects of AD-associated variants on cis-regulatory elements, we train convolutional neural network (CNN) regression models that link genome sequence to cell type-specific levels of open chromatin, a proxy for regulatory element activity. We then use in silico mutagenesis of regulatory sequences to predict the relative impact of candidate variants across these cell types. We develop and apply criteria for evaluating our models and refine our models using massively parallel reporter assay (MPRA) data. Our models identify multiple AD-associated variants with a greater predicted impact in peripheral cells relative to microglia or neurons. Our results support their use as models to study the effects of AD-associated variants and even suggest that peripheral immune cells themselves may mediate a component of AD predisposition. We make our library of CNN models and predictions available as a resource for the community to study immune and neurological disorders.