Single nucleus multiomics identifies ZEB1 and MAFB as candidate regulators of Alzheimer's disease-specific cis-regulatory elements

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.

Cell type-specific multi-omics analysis of cocaine use disorder in the human caudate nucleus

Structural and functional alterations in the brain's reward circuitry are present in cocaine use disorder (CocUD), but their molecular underpinnings remain unclear. To investigate these mechanisms, we performed single-nuclei multiome profiling on postmortem caudate nucleus tissue from six individuals with CocUD and eight controls. We profiled 30,030 nuclei, identifying 13 cell types including D1- and D2-medium spiny neurons (MSNs) and glial cells. We observed 1485 differentially regulated genes and 10,342 differentially accessible peaks, with alterations in MSNs and astrocytes related to neurotransmitter activity and synapse organization. Gene regulatory network analysis identified transcription factors including ZEB1 as exhibiting distinct CocUD-specific subclusters, activating downstream expression of ion- and calcium-channels in MSNs. Further, PDE10A emerged as a potential drug target, showing conserved effects in a rat model. This study highlights cell type-specific molecular alterations in CocUD and provides targets for further investigation, demonstrating the value of multi-omics approaches in addiction research.

Direct hybridization and bioinformatics analysis of circulating microRNAs in patients with Alzheimer's disease under intravenous trehalose treatment

Trehalose has been proposed as a possible therapeutic option for attenuating the neuropathological changes associated with neurodegeneration, including Alzheimer's disease (AD). The administration of trehalose in human and murine models was linked to restoring antioxidant status, decreasing lipoperoxidation, and alleviating neuroinflammation. This latter biochemical mechanism was associated with the upregulation of specific brain-enriched microRNAs (miRNA). Herein, using a direct hybridization approach, we evaluate trehalose intravenous treatment in AD patients, conducting a phase two clinical trial (IRCT20130829014521N15) examining the alteration of microRNA profiles before and after the treatment. Twenty patients were recruited and randomly assigned to two groups: the intervention group received 15 g/week of intravenous trehalose. The control group received placebo in the form of normal saline. The period chosen was 12 weeks. Blood samples were obtained at the beginning and end of the study. Circulating microRNAs expression data between the placebo and treatment groups were assessed using microarray analysis. Subsequently, differentially expressed (DE) miRNAs specific to the trehalose-treated group were identified, and their gene targets were determined by bioinformatics-based approaches. The analysis of DE miRNAs pointed out modulation in unique miRNAs between treatment and placebo groups. Specifically, hsa-miR-1268a, -3605-3p, -555, and -6511a-3p were significantly downregulated, while hsa-miR-324-3p and -539-5p showed significant upregulation. Of the 147 overlapped validated genes identified in the bioinformatics analysis, several are related to autophagy, protein aggregation, oxidative stress, and inflammation. KEGG enrichment pathways reveal regulation of actin cytoskeleton, axon guidance, and neurotrophin signaling pathways. The results identify significant modulation in unique miRNAs in AD patients under trehalose. These findings suggest the potential utility of these microRNAs as biomarkers for trehalose pharmacological monitoring in AD.

Genomic and epigenomic insights into purkinje and granule neurons in Alzheimer's disease and related dementia using single-nucleus multiome analysis

Although the human cerebellum is known to be neuropathologically impaired in Alzheimer's disease (AD) and AD-related dementias (ADRD), the cell type-specific transcriptional and epigenomic changes that contribute to this pathology are not well understood. Here, we report single-nucleus multiome (snRNA-seq and snATAC-seq) analysis of 103,861 nuclei isolated from both cerebellum and frontal cortex of AD/ADRD patients and normal controls. Using peak-to-gene linkage analysis, we identified 431,834 significant linkages between gene expression and cell subtype-specific chromatin accessibility regions enriched for candidate cis-regulatory elements (cCREs). These cCREs were associated with AD/ADRD-specific transcriptomic changes and disease-related gene regulatory networks, especially for RAR Related Orphan Receptor A (RORA) and E74 Like ETS Transcription Factor 1 (ELF1) in cerebellar Purkinje cells and granule cells, respectively. Trajectory analysis of granule cell populations further identified disease-relevant transcription factors, such as RORA, and their regulatory targets. Finally, we pinpointed two likely causal genes, Seizure Related 6 Homolog Like 2 (SEZ6L2) in Purkinje cells and KAT8 Regulatory NSL Complex Subunit 1 (KANSL1) in granule cells, through integrative analysis of cCREs derived from snATAC-seq, genome-wide AD/ADRD loci, and three-dimensional (3D) genome data. Via CRISPRi experiments, we found that perturbation of rs4788201 and rs62056801 significantly inhibited the expression of their target genes, SEZ6L2 and KANSL1, in human iPSC-derived neurons. This cell subtype-specific regulatory landscape in the human cerebellum identified here offers novel genomic and epigenomic insights into the neuropathology and pathobiology of AD/ADRD and other neurological disorders if broadly applied.

Integrative Epigenomic Landscape of Alzheimer's Disease Brains Reveals Oligodendrocyte Molecular Perturbations Associated with Tau

Alzheimer's disease (AD) brains are characterized by neuropathologic and biochemical changes that are highly variable across individuals. Capturing epigenetic factors that associate with this variability can reveal novel biological insights into AD pathophysiology. We conducted an epigenome-wide association study of DNA methylation (DNAm) in 472 AD brains with neuropathologic measures (Braak stage, Thal phase, and cerebral amyloid angiopathy score) and brain biochemical levels of five proteins (APOE, amyloid-β (Aβ)40, Aβ42, tau, and p-tau) core to AD pathogenesis. Using a novel regional methylation (rCpGm) approach, we identified 5,478 significant associations, 99.7% of which were with brain tau biochemical measures. Of the tau-associated rCpGms, 93 had concordant associations in external datasets comprising 1,337 brain samples. Integrative transcriptome-methylome analyses uncovered 535 significant gene expression associations for these 93 rCpGms. Genes with concurrent transcriptome-methylome perturbations were enriched in oligodendrocyte marker genes, including known AD risk genes such as BIN1 , myelination genes MYRF, MBP and MAG previously implicated in AD, as well as novel genes like LDB3 . We further annotated the top oligodendrocyte genes in an additional 6 brain single cell and 2 bulk transcriptome datasets from AD and two other tauopathies, Pick's disease and progressive supranuclear palsy (PSP). Our findings support consistent rCpGm and gene expression associations with these tauopathies and tau-related phenotypes in both bulk brain tissue and oligodendrocyte clusters. In summary, we uncover the integrative epigenomic landscape of AD and demonstrate tau-related oligodendrocyte gene perturbations as a common potential pathomechanism across different tauopathies.

Sex chromosomes and sex hormones differently shape microglial properties during normal physiological conditions in the adult mouse hippocampus

The brain presents various structural and functional sex differences, for which multiple factors are attributed: genetic, epigenetic, metabolic, and hormonal. While biological sex is determined by both sex chromosomes and sex hormones, little is known about how these two factors interact to establish this dimorphism. Sex differences in the brain also affect its resident immune cells, microglia, which actively survey the brain parenchyma and interact with sex hormones throughout life. However, microglial differences in density and distribution, morphology and ultrastructural patterns in physiological conditions during adulthood are largely unknown. Here, we investigated these aforementioned properties of microglia using the Four Core Genotypes (FCG) model, which allows for an independent assessment of gonadal hormones and sex chromosomal effects in four conditions: FCG XX and Tg XY- (both ovaries); Tg XXSry and Tg XYSry (both testes). We also compared the FCG results with XX and XY wild-type (WT) mice. In adult mice, we focused our investigation on the ventral hippocampus across different layers: CA1 stratum radiatum (Rad) and CA1 stratum lacunosum-moleculare (LMol), as well as the dentate gyrus polymorphic layer (PoDG). Double immunostaining for Iba1 and TMEM119 revealed that microglial density is influenced by both sex chromosomes and sex hormones. We show in the Rad and LMol that microglia are denser in FCG XX compared to Tg XYSry mice, however, microglia were densest in WT XX mice. In the PoDG, ovarian animals had increased microglial density compared to testes animals. Additionally, microglial morphology was modulated by a complex interaction between hormones and chromosomes, affecting both their cellular soma and arborization across the hippocampal layers. Moreover, ultrastructural analysis showed that microglia in WT animals make overall more contacts with pre- and post-synaptic elements than in FCG animals. Lastly, microglial markers of cellular stress, including mitochondrion elongation, and dilation of the endoplasmic reticulum and Golgi apparatus, were mostly chromosomally driven. Overall, we characterized different aspects of microglial properties during normal physiological conditions that were found to be shaped by sex chromosomes and sex hormones, shading more light onto how sex differences affect the brain immunity at steady-state.

Machine learning identified novel players in lipid metabolism, endosomal trafficking, and iron metabolism of the ALS spinal cord

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease affecting motor neurons. Although genes causing familial cases have been identified, those of sporadic ALS, which occupies the majority of patients, are still elusive. In this study, we adopted machine learning to build binary classifiers based on the New York Genome Center (NYGC) ALS Consortium's RNA-seq data of the postmortem spinal cord of ALS and non-neurological disease control. The accuracy of the classifiers was greater than 83% and 77% for the training set and the unseen test set, respectively. The classifiers contained 114 genes. Among them, 41 genes have been reported in previous ALS studies, and others are novel in this field. These genes are involved in mitochondrial respiration, lipid metabolism, endosomal trafficking, and iron metabolism, which may promote the progression of ALS pathology.

Comparative mapping of single-cell transcriptomic landscapes in neurodegenerative diseases

INTRODUCTION

Alzheimer's disease (AD), Dementia with Lewy bodies (DLB), and Parkinson's disease (PD) represent a spectrum of neurodegenerative disorders (NDDs). Here, we performed the first direct comparison of their transcriptomic landscapes.

METHODS

We profiled the whole transcriptomes of NDD cortical tissue by snRNA-seq. We used computational analyses to identify common and distinct differentially expressed genes (DEGs), biological pathways, vulnerable and disease-driver cell subtypes, and alteration in cell-to-cell interactions.

RESULTS

The same vulnerable inhibitory neuron subtype was depleted in both AD and DLB. Potentially disease-driving neuronal cell subtypes were present in both PD and DLB. Cell-cell communication was predicted to be increased in AD but decreased in DLB and PD. DEGs were most commonly shared across NDDs within inhibitory neuron subtypes. Overall, we observed the greatest transcriptomic divergence between AD and PD, while DLB exhibited an intermediate transcriptomic signature.

DISCUSSION

These results help explain the clinicopathological spectrum of this group of NDDs and provide unique insights into the shared and distinct molecular mechanisms underlying the pathogenesis of NDDs.

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.

Allele-specific transcription factor binding across human brain regions offers mechanistic insight into eQTLs

Transcription factors (TFs) regulate gene expression by facilitating or disrupting the formation of transcription initiation machinery at particular genomic loci. Because TF occupancy is driven in part by recognition of DNA sequence, genetic variation can influence TF-DNA associations and gene regulation. To identify variants that impact TF binding in human brain tissues, we assessed allele-specific binding (ASB) at heterozygous variants for 94 TFs in nine brain regions from two donors. Leveraging graph genomes constructed from phased genomic sequence data, we compared ChIP-seq signals between alleles at heterozygous variants within each brain region and identified thousands of variants exhibiting ASB for at least one TF. ASB reproducibility was measured by comparisons between independent experiments both within and between donors. We found that rare alleles in the general population more frequently led to reduced TF binding, whereas common alleles had an equal likelihood of increasing or decreasing binding. Further, for ASB variants in predicted binding motifs, the favored allele tended to be the one with the stronger expected motif match, but this concordance was not observed within highly occupied sites. We also found that neuron-specific cis-regulatory elements (cCREs), in contrast with oligodendrocyte-specific cCREs, showed depletion of ASB variants. We identified 2670 ASB variants associated with evidence for allele-specific gene expression in the brain from GTEx data and observed increasing eQTL effect direction concordance as ASB significance increases. These results provide a valuable and unique resource for mechanistic analysis of cis-regulatory variation in human brain tissue.

Integrating large-scale single-cell RNA sequencing in central nervous system disease using self-supervised contrastive learning

The central nervous system (CNS) comprises a diverse range of brain cell types with distinct functions and gene expression profiles. Although single-cell RNA sequencing (scRNA-seq) provides new insights into the brain cell atlases, integrating large-scale CNS scRNA-seq data still encounters challenges due to the complexity and heterogeneity among CNS cell types/subtypes. In this study, we introduce a self-supervised contrastive learning method, called scCM, for integrating large-scale CNS scRNA-seq data. scCM brings functionally related cells close together while simultaneously pushing apart dissimilar cells by comparing the variations of gene expression, effectively revealing the heterogeneous relationships within the CNS cell types/subtypes. The effectiveness of scCM is evaluated on 20 CNS datasets covering 4 species and 10 CNS diseases. Leveraging these strengths, we successfully integrate the collected human CNS datasets into a large-scale reference to annotate cell types and subtypes in neural tissues. Results demonstrate that scCM provides an accurate annotation, along with rich spatial information of cell state. In summary, scCM is a robust and promising method for integrating large-scale CNS scRNA-seq data, enabling researchers to gain insights into the cellular and molecular mechanisms underlying CNS functions and diseases.

Single-nucleus multiome analysis of human cerebellum in Alzheimer's disease-related dementia

Although human cerebellum is known to be neuropathologically impaired in Alzheimer's disease (AD) and AD-related dementias (ADRD), the cell type-specific transcriptional and epigenomic changes that contribute to this pathology are not well understood. Here, we report single-nucleus multiome (snRNA-seq and snATAC-seq) analysis of 103,861 nuclei isolated from cerebellum from 9 human cases of AD/ADRD and 8 controls, and with frontal cortex of 6 AD donors for additional comparison. Using peak-to-gene linkage analysis, we identified 431,834 significant linkages between gene expression and cell subtype-specific chromatin accessibility regions enriched for candidate cis-regulatory elements (cCREs). These cCREs were associated with AD/ADRD-specific transcriptomic changes and disease-related gene regulatory networks, especially for RAR Related Orphan Receptor A (RORA) and E74 Like ETS Transcription Factor 1 (ELF1) in cerebellar Purkinje cells and granule cells, respectively. Trajectory analysis of granule cell populations further identified disease-relevant transcription factors, such as RORA, and their regulatory targets. Finally, we prioritized two likely causal genes, including Seizure Related 6 Homolog Like 2 (SEZ6L2) in Purkinje cells and KAT8 Regulatory NSL Complex Subunit 1 (KANSL1) in granule cells, through integrative analysis of cCREs derived from snATAC-seq, genome-wide AD/ADRD loci, and Hi-C looping data. This first cell subtype-specific regulatory landscape in the human cerebellum identified here offer novel genomic and epigenomic insights into the neuropathology and pathobiology of AD/ADRD and other neurological disorders if broadly applied.

Cell type-specific Multi-Omics Analysis of Cocaine Use Disorder in the Human Caudate Nucleus

Structural and functional alterations in the brain's reward circuitry are present in cocaine use disorder (CocUD), but their molecular underpinnings remain unclear. To investigate these mechanisms, we performed single-nuclei multiome profiling on postmortem caudate nucleus tissue from six individuals with CocUD and eight controls. We profiled 31,178 nuclei, identifying 13 cell types including D1- and D2-medium spiny neurons (MSNs) and glial cells. We observed 1,383 differentially regulated genes and 10,235 differentially accessible peaks, with alterations in MSNs and astrocytes related to neurotransmitter activity and synapse organization. Gene regulatory network analysis identified the transcription factor ZEB1 as exhibiting distinct CocUD-specific subclusters, activating downstream expression of ion- and calcium-channels in MSNs. Further, PDE10A emerged as a potential drug target, showing conserved effects in a rat model. This study highlights cell type-specific molecular alterations in CocUD and provides targets for further investigation, demonstrating the value of multi-omics approaches in addiction research.

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.

Single cell transcriptomes and multiscale networks from persons with and without Alzheimer's disease

The emergence of single nucleus RNA sequencing (snRNA-seq) offers to revolutionize the study of Alzheimer's disease (AD). Integration with complementary multiomics data such as genetics, proteomics and clinical data provides powerful opportunities to link cell subpopulations and molecular networks with a broader disease-relevant context. We report snRNA-seq profiles from superior frontal gyrus samples from 101 well characterized subjects from the Banner Brain and Body Donation Program in combination with whole genome sequences. We report findings that link common AD risk variants with CR1 expression in oligodendrocytes as well as alterations in hematological parameters. We observed an AD-associated CD83(+) microglial subtype with unique molecular networks and which is associated with immunoglobulin IgG4 production in the transverse colon. Our major observations were replicated in two additional, independent snRNA-seq data sets. These findings illustrate the power of multi-tissue molecular profiling to contextualize snRNA-seq brain transcriptomics and reveal disease biology.

Multiomic profiling of transcription factor binding and function in human brain

Transcription factors (TFs) orchestrate gene expression programs crucial for brain function, but we lack detailed information about TF binding in human brain tissue. We generated a multiomic resource (ChIP-seq, ATAC-seq, RNA-seq, DNA methylation) on bulk tissues and sorted nuclei from several postmortem brain regions, including binding maps for more than 100 TFs. We demonstrate improved measurements of TF activity, including motif recognition and gene expression modeling, upon identification and removal of high TF occupancy regions. Further, predictive TF binding models demonstrate a bias for these high-occupancy sites. Neuronal TFs SATB2 and TBR1 bind unique regions depleted for such sites and promote neuronal gene expression. Binding sites for TFs, including TBR1 and PKNOX1, are enriched for risk variants associated with neuropsychiatric disorders, predominantly in neurons. This work, titled BrainTF, is a powerful resource for future studies seeking to understand the roles of specific TFs in regulating gene expression in the human brain.

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.

Systematic Analysis of Biological Processes Reveals Gene Co-expression Modules Driving Pathway Dysregulation in Alzheimer's Disease

Alzheimer's disease (AD) manifests as a complex systems pathology with intricate interplay among various genes and biological processes. Traditional differential gene expression (DEG) analysis, while commonly employed to characterize AD-driven perturbations, does not sufficiently capture the full spectrum of underlying biological processes. Utilizing single-nucleus RNA-sequencing data from postmortem brain samples across key regions-middle temporal gyrus, superior frontal gyrus, and entorhinal cortex-we provide a comprehensive systematic analysis of disrupted processes in AD. We go beyond the DEG-centric analysis by integrating pathway activity analysis with weighted gene co-expression patterns to comprehensively map gene interconnectivity, identifying region- and cell-type-specific drivers of biological processes associated with AD. Our analysis reveals profound modular heterogeneity in neurons and glia as well as extensive AD-related functional disruptions. Co-expression networks highlighted the extended involvement of astrocytes and microglia in biological processes beyond neuroinflammation, such as calcium homeostasis, glutamate regulation, lipid metabolism, vesicle-mediated transport, and TOR signaling. We find limited representation of DEGs within dysregulated pathways across neurons and glial cells, suggesting that differential gene expression alone may not adequately represent the disease complexity. Further dissection of inferred gene modules revealed distinct dynamics of hub DEGs in neurons versus glia, suggesting that DEGs exert more impact on neurons compared to glial cells in driving modular dysregulations underlying perturbed biological processes. Interestingly, we observe an overall downregulation of astrocyte and microglia modules across all brain regions in AD, indicating a prevailing trend of functional repression in glial cells across these regions. Notable genes from the CALM and HSP90 families emerged as hub genes across neuronal modules in all brain regions, suggesting conserved roles as drivers of synaptic dysfunction in AD. Our findings demonstrate the importance of an integrated, systems-oriented approach combining pathway and network analysis to comprehensively understand the cell-type-specific roles of genes in AD-related biological processes.

The broken Alzheimer's disease genome

The complex pathobiology of late-onset Alzheimer's disease (AD) poses significant challenges to therapeutic and preventative interventions. Despite these difficulties, genomics and related disciplines are allowing fundamental mechanistic insights to emerge with clarity, particularly with the introduction of high-resolution sequencing technologies. After all, the disrupted processes at the interface between DNA and gene expression, which we call the broken AD genome, offer detailed quantitative evidence unrestrained by preconceived notions about the disease. In addition to highlighting biological pathways beyond the classical pathology hallmarks, these advances have revitalized drug discovery efforts and are driving improvements in clinical tools. We review genetic, epigenomic, and gene expression findings related to AD pathogenesis and explore how their integration enables a better understanding of the multicellular imbalances contributing to this heterogeneous condition. The frontiers opening on the back of these research milestones promise a future of AD care that is both more personalized and predictive.

Unraveling the genetic architecture of blood unfolded p-53 among non-demented elderlies: novel candidate genes for early Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a heritable neurodegenerative disease whose long asymptomatic phase makes the early diagnosis of it pivotal. Blood U-p53 has recently emerged as a superior predictive biomarker for AD in the early stages. We hypothesized that genetic variants associated with blood U-p53 could reveal novel loci and pathways involved in the early stages of AD.

RESULTS

We performed a blood U-p53 Genome-wide association study (GWAS) on 484 healthy and mild cognitively impaired subjects from the ADNI cohort using 612,843 Single nucleotide polymorphisms (SNPs). We performed a pathway analysis and prioritized candidate genes using an AD single-cell gene program. We fine-mapped the intergenic SNPs by leveraging a cell-type-specific enhancer-to-gene linking strategy using a brain single-cell multimodal dataset. We validated the candidate genes in an independent brain single-cell RNA-seq and the ADNI blood transcriptome datasets. The rs279686 between AASS and FEZF1 genes was the most significant SNP (p-value = 4.82 × 10-7). Suggestive pathways were related to the immune and nervous systems. Twenty-three candidate genes were prioritized at 27 suggestive loci. Fine-mapping of 5 intergenic loci yielded nine cell-specific candidate genes. Finally, 15 genes were validated in the independent single-cell RNA-seq dataset, and five were validated in the ADNI blood transcriptome dataset.

CONCLUSIONS

We underlined the importance of performing a GWAS on an early-stage biomarker of AD and leveraging functional omics datasets for pinpointing causal genes in AD. Our study prioritized nine genes (SORCS1, KIF5C, TMEFF2, TMEM63C, HLA-E, ATAT1, TUBB, ARID1B, and RUNX1) strongly implicated in the early stages of AD.

Gene networks and systems biology in Alzheimer's disease: Insights from multi-omics approaches

Despite numerous studies in the field of dementia and Alzheimer's disease (AD), a comprehensive understanding of this devastating disease remains elusive. Bulk transcriptomics have provided insights into the underlying genetic factors at a high level. Subsequent technological advancements have focused on single-cell omics, encompassing techniques such as single-cell RNA sequencing and epigenomics, enabling the capture of RNA transcripts and chromatin states at a single cell or nucleus resolution. Furthermore, the emergence of spatial omics has allowed the study of gene responses in the vicinity of amyloid beta plaques or across various brain regions. With the vast amount of data generated, utilizing gene regulatory networks to comprehensively study this disease has become essential. This review delves into some techniques employed in the field of AD, explores the discoveries made using these techniques, and provides insights into the future of the field.

Deciphering the cellular heterogeneity of the insect brain with single-cell RNA sequencing

Insects show highly complicated adaptive and sophisticated behaviors, including spatial orientation skills, learning ability, and social interaction. These behaviors are controlled by the insect brain, the central part of the nervous system. The tiny insect brain consists of millions of highly differentiated and interconnected cells forming a complex network. Decades of research has gone into an understanding of which parts of the insect brain possess particular behaviors, but exactly how they modulate these functional consequences needs to be clarified. Detailed description of the brain and behavior is required to decipher the complexity of cell types, as well as their connectivity and function. Single-cell RNA-sequencing (scRNA-seq) has emerged recently as a breakthrough technology to understand the transcriptome at cellular resolution. With scRNA-seq, it is possible to uncover the cellular heterogeneity of brain cells and elucidate their specific functions and state. In this review, we first review the basic structure of insect brains and the links to insect behaviors mainly focusing on learning and memory. Then the scRNA applications on insect brains are introduced by representative studies. Single-cell RNA-seq has allowed researchers to classify cell subpopulations within different insect brain regions, pinpoint single-cell developmental trajectories, and identify gene regulatory networks. These developments empower the advances in neuroscience and shed light on the intricate problems in understanding insect brain functions and behaviors.

Systematic Analysis of Biological Processes Reveals Gene Co-expression Modules Driving Pathway Dysregulation in Alzheimer's Disease

Alzheimer's disease (AD) manifests as a complex systems pathology with intricate interplay among various genes and biological processes. Traditional differential gene expression (DEG) analysis, while commonly employed to characterize AD-driven perturbations, does not sufficiently capture the full spectrum of underlying biological processes. Utilizing single-nucleus RNA-sequencing data from postmortem brain samples across key regions-middle temporal gyrus, superior frontal gyrus, and entorhinal cortex-we provide a comprehensive systematic analysis of disrupted processes in AD. We go beyond the DEG-centric analysis by integrating pathway activity analysis with weighted gene co-expression patterns to comprehensively map gene interconnectivity, identifying region- and cell-type-specific drivers of biological processes associated with AD. Our analysis reveals profound modular heterogeneity in neurons and glia as well as extensive AD-related functional disruptions. Co-expression networks highlighted the extended involvement of astrocytes and microglia in biological processes beyond neuroinflammation, such as calcium homeostasis, glutamate regulation, lipid metabolism, vesicle-mediated transport, and TOR signaling. We find limited representation of DEGs within dysregulated pathways across neurons and glial cells, indicating that differential gene expression alone may not adequately represent the disease complexity. Further dissection of inferred gene modules revealed distinct dynamics of hub DEGs in neurons versus glia, highlighting the differential impact of DEGs on neurons compared to glial cells in driving modular dysregulations underlying perturbed biological processes. Interestingly, we note an overall downregulation of both astrocyte and microglia modules in AD across all brain regions, suggesting a prevailing trend of functional repression in glial cells across these regions. Notable genes, including those of the CALM and HSP90 family genes emerged as hub genes across neuronal modules in all brain regions, indicating conserved roles as drivers of synaptic dysfunction in AD. Our findings demonstrate the importance of an integrated, systems-oriented approach combining pathway and network analysis for a comprehensive understanding of the cell-type-specific roles of genes in AD-related biological processes.

Established and emerging techniques for the study of microglia: visualization, depletion, and fate mapping

The central nervous system (CNS) is an essential hub for neuronal communication. As a major component of the CNS, glial cells are vital in the maintenance and regulation of neuronal network dynamics. Research on microglia, the resident innate immune cells of the CNS, has advanced considerably in recent years, and our understanding of their diverse functions continues to grow. Microglia play critical roles in the formation and regulation of neuronal synapses, myelination, responses to injury, neurogenesis, inflammation, and many other physiological processes. In parallel with advances in microglial biology, cutting-edge techniques for the characterization of microglial properties have emerged with increasing depth and precision. Labeling tools and reporter models are important for the study of microglial morphology, ultrastructure, and dynamics, but also for microglial isolation, which is required to glean key phenotypic information through single-cell transcriptomics and other emerging approaches. Strategies for selective microglial depletion and modulation can provide novel insights into microglia-targeted treatment strategies in models of neuropsychiatric and neurodegenerative conditions, cancer, and autoimmunity. Finally, fate mapping has emerged as an important tool to answer fundamental questions about microglial biology, including their origin, migration, and proliferation throughout the lifetime of an organism. This review aims to provide a comprehensive discussion of these established and emerging techniques, with applications to the study of microglia in development, homeostasis, and CNS pathologies.

Neuronal MAPT expression is mediated by long-range interactions with cis-regulatory elements

Tauopathies are a group of neurodegenerative diseases defined by abnormal aggregates of tau, a microtubule-associated protein encoded by MAPT. MAPT expression is near absent in neural progenitor cells (NPCs) and increases during differentiation. This temporally dynamic expression pattern suggests that MAPT expression could be controlled by transcription factors and cis-regulatory elements specific to differentiated cell types. Given the relevance of MAPT expression to neurodegeneration pathogenesis, identification of such elements is relevant to understanding disease risk and pathogenesis. Here, we performed chromatin conformation assays (HiC & Capture-C), single-nucleus multiomics (RNA-seq+ATAC-seq), bulk ATAC-seq, and ChIP-seq for H3K27ac and CTCF in NPCs and differentiated neurons to nominate candidate cis-regulatory elements (cCREs). We assayed these cCREs using luciferase assays and CRISPR interference (CRISPRi) experiments to measure their effects on MAPT expression. Finally, we integrated cCRE annotations into an analysis of genetic variation in neurodegeneration-affected individuals and control subjects. We identified both proximal and distal regulatory elements for MAPT and confirmed the regulatory function for several regions, including three regions centromeric to MAPT beyond the H1/H2 haplotype inversion breakpoint. We also found that rare and predicted damaging genetic variation in nominated CREs was nominally depleted in dementia-affected individuals relative to control subjects, consistent with the hypothesis that variants that disrupt MAPT enhancer activity, and thereby reduced MAPT expression, may be protective against neurodegenerative disease. Overall, this study provides compelling evidence for pursuing detailed knowledge of CREs for genes of interest to permit better understanding of disease risk.

Mesenchymal Stem Cells from Familial Alzheimer's Patients Express MicroRNA Differently

Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the predominant form of dementia globally. No reliable diagnostic, predictive techniques, or curative interventions are available. MicroRNAs (miRNAs) are vital to controlling gene expression, making them valuable biomarkers for diagnosis and prognosis. This study examines the transcriptome of olfactory ecto-mesenchymal stem cells (MSCs) derived from individuals with the PSEN1(A431E) mutation (Jalisco mutation). The aim is to determine whether this mutation affects the transcriptome and expression profile of miRNAs and their target genes at different stages of asymptomatic, presymptomatic, and symptomatic conditions. Expression microarrays compare the MSCs from mutation carriers with those from healthy donors. The results indicate a distinct variation in the expression of miRNAs and mRNAs among different symptomatologic groups and between individuals with the mutation. Using bioinformatics tools allows us to identify target genes for miRNAs, which in turn affect various biological processes and pathways. These include the cell cycle, senescence, transcription, and pathways involved in regulating the pluripotency of stem cells. These processes are closely linked to inter- and intracellular communication, vital for cellular functioning. These findings can enhance our comprehension and monitoring of the disease's physiological processes, identify new disorder indicators, and develop innovative treatments and diagnostic tools for preventing or treating AD.

Unraveling the intercellular communication disruption and key pathways in Alzheimer's disease: an integrative study of single-nucleus transcriptomes and genetic association

BACKGROUND

Recently, single-nucleus RNA-seq (snRNA-seq) analyses have revealed important cellular and functional features of Alzheimer's disease (AD), a prevalent neurodegenerative disease. However, our knowledge regarding intercellular communication mediated by dysregulated ligand-receptor (LR) interactions remains very limited in AD brains.

METHODS

We systematically assessed the intercellular communication networks by using a discovery snRNA-seq dataset comprising 69,499 nuclei from 48 human postmortem prefrontal cortex (PFC) samples. We replicated the findings using an independent snRNA-seq dataset of 56,440 nuclei from 18 PFC samples. By integrating genetic signals from AD genome-wide association studies (GWAS) summary statistics and whole genome sequencing (WGS) data, we prioritized AD-associated Gene Ontology (GO) terms containing dysregulated LR interactions. We further explored drug repurposing for the prioritized LR pairs using the Therapeutic Targets Database.

RESULTS

We identified 190 dysregulated LR interactions across six major cell types in AD PFC, of which 107 pairs were replicated. Among the replicated LR signals, we found globally downregulated communications in the astrocytes-to-neurons signaling axis, characterized, for instance, by the downregulation of APOE-related and Calmodulin (CALM)-related LR interactions and their potential regulatory connections to target genes. Pathway analyses revealed 44 GO terms significantly linked to AD, highlighting Biological Processes such as 'amyloid precursor protein processing' and 'ion transmembrane transport,' among others. We prioritized several drug repurposing candidates, such as cromoglicate, targeting the identified dysregulated LR pairs.

CONCLUSIONS

Our integrative analysis identified key dysregulated LR interactions in a cell type-specific manner and the associated GO terms in AD, offering novel insights into potential therapeutic targets involved in disrupted cell-cell communication in AD.

Gene regulatory network inference in the era of single-cell multi-omics

The interplay between chromatin, transcription factors and genes generates complex regulatory circuits that can be represented as gene regulatory networks (GRNs). The study of GRNs is useful to understand how cellular identity is established, maintained and disrupted in disease. GRNs can be inferred from experimental data - historically, bulk omics data - and/or from the literature. The advent of single-cell multi-omics technologies has led to the development of novel computational methods that leverage genomic, transcriptomic and chromatin accessibility information to infer GRNs at an unprecedented resolution. Here, we review the key principles of inferring GRNs that encompass transcription factor-gene interactions from transcriptomics and chromatin accessibility data. We focus on the comparison and classification of methods that use single-cell multimodal data. We highlight challenges in GRN inference, in particular with respect to benchmarking, and potential further developments using additional data modalities.

A public resource of single cell transcriptomes and multiscale networks from persons with and without Alzheimer's disease

The emergence of technologies that can support high-throughput profiling of single cell transcriptomes offers to revolutionize the study of brain tissue from persons with and without Alzheimer's disease (AD). Integration of these data with additional complementary multiomics data such as genetics, proteomics and clinical data provides powerful opportunities to link observed cell subpopulations and molecular network features within a broader disease-relevant context. We report here single nucleus RNA sequencing (snRNA-seq) profiles generated from superior frontal gyrus cortical tissue samples from 101 exceptionally well characterized, aged subjects from the Banner Brain and Body Donation Program in combination with whole genome sequences. We report findings that link common AD risk variants with CR1 expression in oligodendrocytes as well as alterations in peripheral hematological lab parameters, with these observations replicated in an independent, prospective cohort study of ageing and dementia. We also observed an AD-associated CD83(+) microglial subtype with unique molecular networks that encompass many known regulators of AD-relevant microglial biology, and which are associated with immunoglobulin IgG4 production in the transverse colon. These findings illustrate the power of multi-tissue molecular profiling to contextualize snRNA-seq brain transcriptomics and reveal novel disease biology. The transcriptomic, genetic, phenotypic, and network data resources described within this study are available for access and utilization by the scientific community.

Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer's disease brains

BACKGROUND

The genetic underpinnings of late-onset Alzheimer's disease (LOAD) are yet to be fully elucidated. Although numerous LOAD-associated loci have been discovered, the causal variants and their target genes remain largely unknown. Since the brain is composed of heterogenous cell subtypes, it is imperative to study the brain on a cell subtype specific level to explore the biological processes underlying LOAD.

METHODS

Here, we present the largest parallel single-nucleus (sn) multi-omics study to simultaneously profile gene expression (snRNA-seq) and chromatin accessibility (snATAC-seq) to date, using nuclei from 12 normal and 12 LOAD brains. We identified cell subtype clusters based on gene expression and chromatin accessibility profiles and characterized cell subtype-specific LOAD-associated differentially expressed genes (DEGs), differentially accessible peaks (DAPs) and cis co-accessibility networks (CCANs).

RESULTS

Integrative analysis defined disease-relevant CCANs in multiple cell subtypes and discovered LOAD-associated cell subtype-specific candidate cis regulatory elements (cCREs), their candidate target genes, and trans-interacting transcription factors (TFs), some of which, including ELK1, JUN, and SMAD4 in excitatory neurons, were also LOAD-DEGs. Finally, we focused on a subset of cell subtype-specific CCANs that overlap known LOAD-GWAS regions and catalogued putative functional SNPs changing the affinities of TF motifs within LOAD-cCREs linked to LOAD-DEGs, including APOE and MYO1E in a specific subtype of microglia and BIN1 in a subpopulation of oligodendrocytes.

CONCLUSIONS

To our knowledge, this study represents the most comprehensive systematic interrogation to date of regulatory networks and the impact of genetic variants on gene dysregulation in LOAD at a cell subtype resolution. Our findings reveal crosstalk between epigenetic, genomic, and transcriptomic determinants of LOAD pathogenesis and define catalogues of candidate genes, cCREs, and variants involved in LOAD genetic etiology and the cell subtypes in which they act to exert their pathogenic effects. Overall, these results suggest that cell subtype-specific cis-trans interactions between regulatory elements and TFs, and the genes dysregulated by these networks contribute to the development of LOAD.

Polygenic regression uncovers trait-relevant cellular contexts through pathway activation transformation of single-cell RNA sequencing data

Advances in single-cell RNA sequencing (scRNA-seq) techniques have accelerated functional interpretation of disease-associated variants discovered from genome-wide association studies (GWASs). However, identification of trait-relevant cell populations is often impeded by inherent technical noise and high sparsity in scRNA-seq data. Here, we developed scPagwas, a computational approach that uncovers trait-relevant cellular context by integrating pathway activation transformation of scRNA-seq data and GWAS summary statistics. scPagwas effectively prioritizes trait-relevant genes, which facilitates identification of trait-relevant cell types/populations with high accuracy in extensive simulated and real datasets. Cellular-level association results identified a novel subpopulation of naive CD8+ T cells related to COVID-19 severity and oligodendrocyte progenitor cell and microglia subsets with critical pathways by which genetic variants influence Alzheimer's disease. Overall, our approach provides new insights for the discovery of trait-relevant cell types and improves the mechanistic understanding of disease variants from a pathway perspective.

Unraveling the intercellular communication disruption and key pathways in Alzheimer's disease: An integrative study of single-nucleus transcriptomes and genetic association

Background

Recently, single-nucleus RNA-seq (snRNA-seq) analyses have revealed important cellular and functional features of Alzheimer's disease (AD), a prevalent neurodegenerative disease. However, our knowledge regarding intercellular communication mediated by dysregulated ligand-receptor (LR) interactions remains very limited in AD brains.

Methods

We systematically assessed the intercellular communication networks by using a discovery snRNA-seq dataset comprising 69,499 nuclei from 48 human postmortem prefrontal cortex (PFC) samples. We replicated the findings using an independent snRNA-seq dataset of 56,440 nuclei from 18 PFC samples. By integrating genetic signals from AD genome-wide association studies (GWAS) summary statistics and whole genome sequencing (WGS) data, we prioritized AD-associated Gene Ontology (GO) terms containing dysregulated LR interactions. We further explored drug repurposing for the prioritized LR pairs using the Therapeutic Targets Database.

Results

We identified 316 dysregulated LR interactions across six major cell types in AD PFC, of which 210 pairs were replicated. Among the replicated LR signals, we found globally downregulated communications in astrocytes-to-neurons signaling axis, characterized, for instance, by the downregulation of APOE-related and Calmodulin (CALM)-related LR interactions and their potential regulatory connections to target genes. Pathway analyses revealed 60 GO terms significantly linked to AD, highlighting Biological Processes such as 'amyloid precursor protein processing' and 'ion transmembrane transport', among others. We prioritized several drug repurposing candidates, such as cromoglicate, targeting the identified dysregulated LR pairs.

Conclusions

Our integrative analysis identified key dysregulated LR interactions in a cell type-specific manner and the associated GO terms in AD, offering novel insights into potential therapeutic targets involved in disrupted cell-cell communication in AD.

Single-Cell Sequencing in Neurodegenerative Disorders

Neurodegenerative disorders are typically characterized by late onset progressive damage to specific (sub)populations of cells of the nervous system that are essential for mobility, coordination, strength, sensation, and cognition. Addressing this selective cellular vulnerability has become feasible with the emergence of single-cell-omics technologies, which now represent the state-of-the-art approach to profile heterogeneity of complex tissues including human post-mortem brain at unprecedented resolution. In this review, we briefly recapitulate the experimental workflow of single-cell RNA sequencing and summarize the recent knowledge acquired with it in the most common neurodegenerative diseases: Parkinson's, Alzheimer's, Huntington's disease, and multiple sclerosis. We also discuss the possibility of applying single-cell approaches in the diagnostics and therapy of neurodegenerative disorders, as well as the limitations. While we are currently at the point of deeply exploring the transcriptomic changes in the affected cells, further technological developments hold a promise of manipulating the affected pathways once we understand them better.

Emerging diagnostics and therapeutics for Alzheimer disease

Alzheimer disease (AD) is the most common contributor to dementia in the world, but strategies that slow or prevent its clinical progression have largely remained elusive, until recently. This Review highlights the latest advances in biomarker technologies and therapeutic development to improve AD diagnosis and treatment. We review recent results that enable pathological staging of AD with neuroimaging and fluid-based biomarkers, with a particular emphasis on the role of amyloid, tau and neuroinflammation in disease pathogenesis. We discuss the lessons learned from randomized controlled trials, including some supporting the proposal that certain anti-amyloid antibodies slow cognitive decline during the mildly symptomatic phase of AD. In addition, we highlight evidence for newly identified therapeutic targets that may be able to modify AD pathogenesis and progression. Collectively, these recent discoveries-and the research directions that they open-have the potential to move AD clinical care toward disease-modifying treatment strategies with maximal benefits for patients.

Genetic associations with age at dementia onset in the PSEN1 E280A Colombian kindred

INTRODUCTION

Genetic associations with Alzheimer's disease (AD) age at onset (AAO) could reveal genetic variants with therapeutic applications. We present a large Colombian kindred with autosomal dominant AD (ADAD) as a unique opportunity to discover AAO genetic associations.

METHODS

A genetic association study was conducted to examine ADAD AAO in 340 individuals with the PSEN1 E280A mutation via TOPMed array imputation. Replication was assessed in two ADAD cohorts, one sporadic early-onset AD study and four late-onset AD studies.

RESULTS

13 variants had p<1×10-7 or p<1×10-5 with replication including three independent loci with candidate associations with clusterin including near CLU. Other suggestive associations were identified in or near HS3ST1, HSPG2, ACE, LRP1B, TSPAN10, and TSPAN14.

DISCUSSION

Variants with suggestive associations with AAO were associated with biological processes including clusterin, heparin sulfate, and amyloid processing. The detection of these effects in the presence of a strong mutation for ADAD reinforces their potentially impactful role.

Spatial and single-nucleus transcriptomic analysis of genetic and sporadic forms of Alzheimer's Disease

The pathogenesis of Alzheimer's disease (AD) depends on environmental and heritable factors, with remarkable differences evident between individuals at the molecular level. Here we present a transcriptomic survey of AD using spatial transcriptomics (ST) and single-nucleus RNA-seq in cortical samples from early-stage AD, late-stage AD, and AD in Down Syndrome (AD in DS) donors. Studying AD in DS provides an opportunity to enhance our understanding of the AD transcriptome, potentially bridging the gap between genetic mouse models and sporadic AD. Our analysis revealed spatial and cell-type specific changes in disease, with broad similarities in these changes between sAD and AD in DS. We performed additional ST experiments in a disease timecourse of 5xFAD and wildtype mice to facilitate cross-species comparisons. Finally, amyloid plaque and fibril imaging in the same tissue samples used for ST enabled us to directly link changes in gene expression with accumulation and spread of pathology.

Impact of non-neuronal cells in Alzheimer's disease from a single-nucleus profiling perspective

The role of non-neuronal cells has been relatively overlooked in Alzheimer's disease (AD) neuropathogenesis compared to neuronal cells since the first characterization of the disease. Genome wide-association studies (GWAS) performed in the last few decades have greatly contributed to highlighting the critical impact of non-neuronal cells in AD by uncovering major genetic risk factors that are found largely in these cell types. The recent development of single cell or single nucleus technologies has revolutionized the way we interrogate the transcriptomic and epigenetic profiles of neurons, microglia, astrocytes, oligodendrocytes, pericytes, and endothelial cells simultaneously in the same sample and in an individual manner. Here, we review the latest advances in single-cell/nucleus RNA sequencing and Assay for Transposase-Accessible Chromatin (ATAC) sequencing to more accurately understand the function of non-neuronal cells in AD. We conclude by giving an overview of what still needs to be achieved to better appreciate the interconnected roles of each cell type in the context of AD.

MAPT expression is mediated by long-range interactions with cis-regulatory elements

Background

Tauopathies are a group of neurodegenerative diseases driven by abnormal aggregates of tau, a microtubule associated protein encoded by the MAPT gene. MAPT expression is absent in neural progenitor cells (NPCs) and increases during differentiation. This temporally dynamic expression pattern suggests that MAPT expression is controlled by transcription factors and cis-regulatory elements specific to differentiated cell types. Given the relevance of MAPT expression to neurodegeneration pathogenesis, identification of such elements is relevant to understanding genetic risk factors.

Methods

We performed HiC, chromatin conformation capture (Capture-C), single-nucleus multiomics (RNA-seq+ATAC-seq), bulk ATAC-seq, and ChIP-seq for H3K27Ac and CTCF in NPCs and neurons differentiated from human iPSC cultures. We nominated candidate cis-regulatory elements (cCREs) for MAPT in human NPCs, differentiated neurons, and pure cultures of inhibitory and excitatory neurons. We then assayed these cCREs using luciferase assays and CRISPR interference (CRISPRi) experiments to measure their effects on MAPT expression. Finally, we integrated cCRE annotations into an analysis of genetic variation in AD cases and controls.

Results

Using orthogonal genomics approaches, we nominated 94 cCREs for MAPT, including the identification of cCREs specifically active in differentiated neurons. Eleven regions enhanced reporter gene transcription in luciferase assays. Using CRISPRi, 5 of the 94 regions tested were identified as necessary for MAPT expression as measured by RT-qPCR and RNA-seq. Rare and predicted damaging genetic variation in both nominated and confirmed CREs was depleted in AD cases relative to controls (OR = 0.40, p = 0.004), consistent with the hypothesis that variants that disrupt MAPT enhancer activity, and thereby reduce MAPT expression, may be protective against neurodegenerative disease.

Conclusions

We identified both proximal and distal regulatory elements for MAPT and confirmed the regulatory function for several regions, including three regions centromeric to MAPT beyond the well-described H1/H2 haplotype inversion breakpoint. This study provides compelling evidence for pursuing detailed knowledge of CREs for genes of interest to permit better understanding of disease risk.