Cellular communities reveal trajectories of brain ageing and Alzheimer's disease.

Alzheimer's disease (AD) has recently been associated with diverse cell states1-11, yet when and how these states affect the onset of AD remains unclear. Here we used a data-driven approach to reconstruct the dynamics of the brain's cellular environment and identified a trajectory leading to AD that is distinct from other ageing-related effects. First, we built a comprehensive cell atlas of the aged prefrontal cortex from 1.65 million single-nucleus RNA-sequencing profiles sampled from 437 older individuals, and identified specific glial and neuronal subpopulations associated with AD-related traits. Causal modelling then prioritized two distinct lipid-associated microglial subpopulations-one drives amyloid-ß proteinopathy while the other mediates the effect of amyloid-ß on tau proteinopathy-as well as an astrocyte subpopulation that mediates the effect of tau on cognitive decline. To model the dynamics of cellular environments, we devised the BEYOND methodology, which identified two distinct trajectories of brain ageing, each defined by coordinated progressive changes in certain cellular communities that lead to (1) AD dementia or (2) alternative brain ageing. Thus, we provide a cellular foundation for a new perspective on AD pathophysiology that informs personalized therapeutic development, targeting different cellular communities for individuals on the path to AD or to alternative brain ageing.

Cell subtype-specific effects of genetic variation in the Alzheimer's disease brain.

The relationship between genetic variation and gene expression in brain cell types and subtypes remains understudied. Here, we generated single-nucleus RNA sequencing data from the neocortex of 424 individuals of advanced age; we assessed the effect of genetic variants on RNA expression in cis (cis-expression quantitative trait loci) for seven cell types and 64 cell subtypes using 1.5 million transcriptomes. This effort identified 10,004 eGenes at the cell type level and 8,099 eGenes at the cell subtype level. Many eGenes are only detected within cell subtypes. A new variant influences APOE expression only in microglia and is associated with greater cerebral amyloid angiopathy but not Alzheimer's disease pathology, after adjusting for APOEε4, providing mechanistic insights into both pathologies. Furthermore, only a TMEM106B variant affects the proportion of cell subtypes. Integration of these results with genome-wide association studies highlighted the targeted cell type and probable causal gene within Alzheimer's disease, schizophrenia, educational attainment and Parkinson's disease loci.

A Single-Nucleus Transcriptome-Wide Association Study Implicates Novel Genes in Depression Pathogenesis.

BACKGROUND: Depression, a common psychiatric illness and global public health problem, remains poorly understood across different life stages, which hampers the development of novel treatments. METHODS: To identify new candidate genes for therapeutic development, we performed differential gene expression analysis of single-nucleus RNA sequencing data from the dorsolateral prefrontal cortex of older adults (n = 424) in relation to antemortem depressive symptoms. Additionally, we integrated genome-wide association study results for depression (n = 500,199) along with genetic tools for inferring the expression of 14,048 unique genes in 7 cell types and 52 cell subtypes to perform a transcriptome-wide association study of depression followed by Mendelian randomization. RESULTS: Our single-nucleus transcriptome-wide association study analysis identified 68 candidate genes for depression and showed the greatest number being in excitatory and inhibitory neurons. Of the 68 genes, 53 were novel compared to previous studies. Notably, gene expression in different neuronal subtypes had varying effects on depression risk. Traits with high genetic correlations with depression, such as neuroticism, shared more transcriptome-wide association study genes than traits that were not highly correlated with depression. Complementing these analyses, differential gene expression analysis across 52 neocortical cell subtypes showed that genes such as KCNN2, SCAI, WASF3, and SOCS6 were associated with late-life depressive symptoms in specific cell subtypes. CONCLUSIONS: These 2 sets of analyses illustrate the utility of large single-nucleus RNA sequencing data both to uncover genes whose expression is altered in specific cell subtypes in the context of depressive symptoms and to enhance the interpretation of well-powered genome-wide association studies so that we can prioritize specific susceptibility genes for further analysis and therapeutic development.

Deep brain stimulation of thalamic nucleus reuniens promotes neuronal and cognitive resilience in an Alzheimer's disease mouse model.

The mechanisms that confer cognitive resilience to Alzheimer's Disease (AD) are not fully understood. Here, we describe a neural circuit mechanism underlying this resilience in a familial AD mouse model. In the prodromal disease stage, interictal epileptiform spikes (IESs) emerge during anesthesia in the CA1 and mPFC regions, leading to working memory disruptions. These IESs are driven by inputs from the thalamic nucleus reuniens (nRE). Indeed, tonic deep brain stimulation of the nRE (tDBS-nRE) effectively suppresses IESs and restores firing rate homeostasis under anesthesia, preventing further impairments in nRE-CA1 synaptic facilitation and working memory. Notably, applying tDBS-nRE during the prodromal phase in young APP/PS1 mice mitigates age-dependent memory decline. The IES rate during anesthesia in young APP/PS1 mice correlates with later working memory impairments. These findings highlight the nRE as a central hub of functional resilience and underscore the clinical promise of DBS in conferring resilience to AD pathology by restoring circuit-level homeostasis.

Molecular Connectomics Reveals a Glucagon-Like Peptide 1 Sensitive Neural Circuit for Satiety.

Liraglutide and other agonists of the glucagon-like peptide 1 receptor (GLP-1RAs) are effective weight loss drugs, but how they suppress appetite remains unclear. GLP-1RAs inhibit hunger-promoting Agouti-related peptide (AgRP) neurons of the arcuate hypothalamus (Arc) but only indirectly, implicating synaptic afferents to AgRP neurons. To investigate, we developed a method combining rabies-based connectomics with single-nuclei transcriptomics. Applying this method to AgRP neurons in mice predicts 21 afferent subtypes in the mediobasal and paraventricular hypothalamus. Among these are Trh+ Arc neurons (TrhArc), which express the Glp1r gene and are activated by the GLP-1RA liraglutide. Activating TrhArc neurons inhibits AgRP neurons and decreases feeding in an AgRP neuron-dependent manner. Silencing TrhArc neurons increases feeding and body weight and reduces liraglutide's satiating effects. Our results thus demonstrate a widely applicable method for molecular connectomics, reveal the molecular organization of AgRP neuron afferents, and shed light on a neurocircuit through which GLP-1RAs suppress appetite.

Non-invasive assessment of normal and impaired iron homeostasis in the brain.

Strict iron regulation is essential for normal brain function. The iron homeostasis, determined by the milieu of available iron compounds, is impaired in aging, neurodegenerative diseases and cancer. However, non-invasive assessment of different molecular iron environments implicating brain tissue's iron homeostasis remains a challenge. We present a magnetic resonance imaging (MRI) technology sensitive to the iron homeostasis of the living brain (the r1-r2* relaxivity). In vitro, our MRI approach reveals the distinct paramagnetic properties of ferritin, transferrin and ferrous iron ions. In the in vivo human brain, we validate our approach against ex vivo iron compounds quantification and gene expression. Our approach varies with the iron mobilization capacity across brain regions and in aging. It reveals brain tumors' iron homeostasis, and enhances the distinction between tumor tissue and non-pathological tissue without contrast agents. Therefore, our approach may allow for non-invasive research and diagnosis of iron homeostasis in living human brains.

Multicellular communities are perturbed in the aging human brain and Alzheimer's disease.

The role of different cell types and their interactions in Alzheimer's disease (AD) is a complex and open question. Here, we pursued this question by assembling a high-resolution cellular map of the aging frontal cortex using single-nucleus RNA sequencing of 24 individuals with a range of clinicopathologic characteristics. We used this map to infer the neocortical cellular architecture of 638 individuals profiled by bulk RNA sequencing, providing the sample size necessary for identifying statistically robust associations. We uncovered diverse cell populations associated with AD, including a somatostatin inhibitory neuronal subtype and oligodendroglial states. We further identified a network of multicellular communities, each composed of coordinated subpopulations of neuronal, glial and endothelial cells, and we found that two of these communities are altered in AD. Finally, we used mediation analyses to prioritize cellular changes that might contribute to cognitive decline. Thus, our deconstruction of the aging neocortex provides a roadmap for evaluating the cellular microenvironments underlying AD and dementia.

Claustral neurons projecting to frontal cortex restrict opioid consumption.

The synthetic opioid fentanyl is a major contributor to the current opioid addiction crisis. We report that claustral neurons projecting to the frontal cortex limit oral fentanyl self-administration in mice. We found that fentanyl transcriptionally activates frontal-projecting claustrum neurons. These neurons also exhibit a unique suppression of Ca2+ activity upon initiation of bouts of fentanyl consumption. Optogenetic stimulation of frontal-projecting claustral neurons, intervening in this suppression, decreased bouts of fentanyl consumption. In contrast, constitutive inhibition of frontal-projecting claustral neurons in the context of a novel, group-housed self-administration procedure increased fentanyl bout consumption. This same manipulation also sensitized conditioned-place preference for fentanyl and enhanced the representation of fentanyl experience in the frontal cortex. Together, our results indicate that claustrum neurons exert inhibitory control over frontal cortical neurons to restrict oral fentanyl intake. Upregulation of activity in the claustro-frontal projection may be a promising strategy for reducing human opioid addiction.

A single-nucleus transcriptome-wide association study implicates novel genes in depression pathogenesis.

Background: Depression is a common psychiatric illness and global public health problem. However, our limited understanding of the biological basis of depression has hindered the development of novel treatments and interventions. Methods: To identify new candidate genes for therapeutic development, we examined single-nucleus RNA sequencing (snucRNAseq) data from the dorsolateral prefrontal cortex (N=424) in relation to ante-mortem depressive symptoms. To complement these direct analyses, we also used genome-wide association study (GWAS) results for depression (N=500,199) along with genetic tools for inferring the expression of 22,159 genes in 7 cell types and 55 cell subtypes to perform transcriptome-wide association studies (TWAS) of depression followed by Mendelian randomization (MR). Results: Our single-nucleus TWAS analysis identified 71 causal genes in depression that have a role in specific neocortical cell subtypes; 59 of 71 genes were novel compared to previous studies. Depression TWAS genes showed a cell type specific pattern, with the greatest enrichment being in both excitatory and inhibitory neurons as well as astrocytes. Gene expression in different neuron subtypes have different directions of effect on depression risk. Compared to lower genetically correlated traits (e.g. body mass index) with depression, higher correlated traits (e.g., neuroticism) have more common TWAS genes with depression. In parallel, we performed differential gene expression analysis in relation to depression in 55 cortical cell subtypes, and we found that genes such as ANKRD36, MADD, TAOK3, SCAI and CHUK are associated with depression in specific cell subtypes. Conclusions: These two sets of analyses illustrate the utility of large snucRNAseq data to uncover both genes whose expression is altered in specific cell subtypes in the context of depression and to enhance the interpretation of well-powered GWAS so that we can prioritize specific susceptibility genes for further analysis and therapeutic development.

N-acetylneuraminic acid links immune exhaustion and accelerated memory deficit in diet-induced obese Alzheimer's disease mouse model.

Systemic immunity supports lifelong brain function. Obesity posits a chronic burden on systemic immunity. Independently, obesity was shown as a risk factor for Alzheimer's disease (AD). Here we show that high-fat obesogenic diet accelerated recognition-memory impairment in an AD mouse model (5xFAD). In obese 5xFAD mice, hippocampal cells displayed only minor diet-related transcriptional changes, whereas the splenic immune landscape exhibited aging-like CD4+ T-cell deregulation. Following plasma metabolite profiling, we identified free N-acetylneuraminic acid (NANA), the predominant sialic acid, as the metabolite linking recognition-memory impairment to increased splenic immune-suppressive cells in mice. Single-nucleus RNA-sequencing revealed mouse visceral adipose macrophages as a potential source of NANA. In vitro, NANA reduced CD4+ T-cell proliferation, tested in both mouse and human. In vivo, NANA administration to standard diet-fed mice recapitulated high-fat diet effects on CD4+ T cells and accelerated recognition-memory impairment in 5xFAD mice. We suggest that obesity accelerates disease manifestation in a mouse model of AD via systemic immune exhaustion.

Cellular dynamics across aged human brains uncover a multicellular cascade leading to Alzheimer's disease.

Alzheimer's Disease (AD) is a progressive neurodegenerative disease seen with advancing age. Recent studies have revealed diverse AD-associated cell states, yet when and how they impact the causal chain leading to AD remains unknown. To reconstruct the dynamics of the brain's cellular environment along the disease cascade and to distinguish between AD and aging effects, we built a comprehensive cell atlas of the aged prefrontal cortex from 1.64 million single-nucleus RNA-seq profiles. We associated glial, vascular and neuronal subpopulations with AD-related traits for 424 aging individuals, and aligned them along the disease cascade using causal modeling. We identified two distinct lipid-associated microglial subpopulations, one contributed to amyloid-ß proteinopathy while the other mediated the effect of amyloid-ß in accelerating tau proteinopathy, as well as an astrocyte subpopulation that mediated the effect of tau on cognitive decline. To model the coordinated dynamics of the entire cellular environment we devised the BEYOND methodology which uncovered two distinct trajectories of brain aging that are defined by distinct sequences of changes in cellular communities. Older individuals are engaged in one of two possible trajectories, each associated with progressive changes in specific cellular communities that end with: (1) AD dementia or (2) alternative brain aging. Thus, we provide a cellular foundation for a new perspective of AD pathophysiology that could inform the development of new therapeutic interventions targeting cellular communities, while designing a different clinical management for those individuals on the path to AD or to alternative brain aging.

High-throughput morphometric and transcriptomic profiling uncovers composition of naïve and sensory-deprived cortical cholinergic VIP/CHAT neurons.

Cortical neuronal networks control cognitive output, but their composition and modulation remain elusive. Here, we studied the morphological and transcriptional diversity of cortical cholinergic VIP/ChAT interneurons (VChIs), a sparse population with a largely unknown function. We focused on VChIs from the whole barrel cortex and developed a high-throughput automated reconstruction framework, termed PopRec, to characterize hundreds of VChIs from each mouse in an unbiased manner, while preserving 3D cortical coordinates in multiple cleared mouse brains, accumulating thousands of cells. We identified two fundamentally distinct morphological types of VChIs, bipolar and multipolar that differ in their cortical distribution and general morphological features. Following mild unilateral whisker deprivation on postnatal day seven, we found after three weeks both ipsi- and contralateral dendritic arborization differences and modified cortical depth and distribution patterns in the barrel fields alone. To seek the transcriptomic drivers, we developed NuNeX, a method for isolating nuclei from fixed tissues, to explore sorted VChIs. This highlighted differentially expressed neuronal structural transcripts, altered exitatory innervation pathways and established Elmo1 as a key regulator of morphology following deprivation.

Stroke genetics informs drug discovery and risk prediction across ancestries.

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.

Single cell biology-a Keystone Symposia report.

Single cell biology has the potential to elucidate many critical biological processes and diseases, from development and regeneration to cancer. Single cell analyses are uncovering the molecular diversity of cells, revealing a clearer picture of the variation among and between different cell types. New techniques are beginning to unravel how differences in cell state-transcriptional, epigenetic, and other characteristics-can lead to different cell fates among genetically identical cells, which underlies complex processes such as embryonic development, drug resistance, response to injury, and cellular reprogramming. Single cell technologies also pose significant challenges relating to processing and analyzing vast amounts of data collected. To realize the potential of single cell technologies, new computational approaches are needed. On March 17-19, 2021, experts in single cell biology met virtually for the Keystone eSymposium "Single Cell Biology" to discuss advances both in single cell applications and technologies.

Early sample tagging and pooling enables simultaneous SARS-CoV-2 detection and variant sequencing.

Most severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostic tests have relied on RNA extraction followed by reverse transcription quantitative polymerase chain reaction (RT-qPCR) assays. Whereas automation improved logistics and different pooling strategies increased testing capacity, highly multiplexed next-generation sequencing (NGS) diagnostics remain a largely untapped resource. NGS tests have the potential to markedly increase throughput while providing crucial SARS-CoV-2 variant information. Current NGS-based detection and genotyping assays for SARS-CoV-2 are costly, mostly due to parallel sample processing through multiple steps. Here, we have established ApharSeq, in which samples are barcoded in the lysis buffer and pooled before reverse transcription. We validated this assay by applying ApharSeq to more than 500 clinical samples from the Clinical Virology Laboratory at Hadassah hospital in a robotic workflow. The assay was linear across five orders of magnitude, and the limit of detection was Ct 33 (~1000 copies/ml, 95% sensitivity) with >99.5% specificity. ApharSeq provided targeted high-confidence genotype information due to unique molecular identifiers incorporated into this method. Because of early pooling, we were able to estimate a 10- to 100-fold reduction in labor, automated liquid handling, and reagent requirements in high-throughput settings compared to current testing methods. The protocol can be tailored to assay other host or pathogen RNA targets simultaneously. These results suggest that ApharSeq can be a promising tool for current and future mass diagnostic challenges.

A cellular and spatial map of the choroid plexus across brain ventricles and ages.

The choroid plexus (ChP) in each brain ventricle produces cerebrospinal fluid (CSF) and forms the blood-CSF barrier. Here, we construct a single-cell and spatial atlas of each ChP in the developing, adult, and aged mouse brain. We delineate diverse cell types, subtypes, cell states, and expression programs in epithelial and mesenchymal cells across ages and ventricles. In the developing ChP, we predict a common progenitor pool for epithelial and neuronal cells, validated by lineage tracing. Epithelial and fibroblast cells show regionalized expression by ventricle, starting at embryonic stages and persisting with age, with a dramatic transcriptional shift with maturation, and a smaller shift in each aged cell type. With aging, epithelial cells upregulate host-defense programs, and resident macrophages upregulate interleukin-1ß (IL-1ß) signaling genes. Our atlas reveals cellular diversity, architecture and signaling across ventricles during development, maturation, and aging of the ChP-brain barrier.

Single cell RNA sequencing of human microglia uncovers a subset associated with Alzheimer's disease.

The extent of microglial heterogeneity in humans remains a central yet poorly explored question in light of the development of therapies targeting this cell type. Here, we investigate the population structure of live microglia purified from human cerebral cortex samples obtained at autopsy and during neurosurgical procedures. Using single cell RNA sequencing, we find that some subsets are enriched for disease-related genes and RNA signatures. We confirm the presence of four of these microglial subpopulations histologically and illustrate the utility of our data by characterizing further microglial cluster 7, enriched for genes depleted in the cortex of individuals with Alzheimer's disease (AD). Histologically, these cluster 7 microglia are reduced in frequency in AD tissue, and we validate this observation in an independent set of single nucleus data. Thus, our live human microglia identify a range of subtypes, and we prioritize one of these as being altered in AD.

Author Correction: Nuclei multiplexing with barcoded antibodies for single-nucleus genomics.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.