Explore the vast range of titles available.

The role of non-neuronal cells in Alzheimer’s disease progression has not been fully elucidated. Using single-nucleus RNA sequencing, we identified a population of disease-associated astrocytes in an Alzheimer’s disease mouse model. These disease-associated astrocytes appeared at early disease stages and increased in abundance with disease progression. We discovered that similar astrocytes appeared in aged wild-type mice and in aging human brains, suggesting their linkage to genetic and age-related factors.A new subset of disease-associated astrocytes (DAAs) is identified in a mouse model of Alzheimer’s disease by single-nucleus RNA sequencing. DAAs are also found in aged wild-type mice, suggesting a link to genetic and age-related factors.

This paper reports the availability of a new Resource with RNA-seq, DNA methylation and H3K9Ac QTL results from 411 brain samples. Many xQTL SNPs influence multiple molecular features, and the authors observe epigenetic mediation of eQTLs in some cases. Reanalyzing GWAS with an xQTL-weighted approach detected 20 new CNS disease susceptibility loci. We report a multi-omic resource generated by applying quantitative trait locus (xQTL) analyses to RNA sequence, DNA methylation and histone acetylation data from the dorsolateral prefrontal cortex of 411 older adults who have all three data types. We identify SNPs significantly associated with gene expression, DNA methylation and histone modification levels. Many of these SNPs influence multiple molecular features, and we demonstrate that SNP effects on RNA expression are fully mediated by epigenetic features in 9% of these loci. Further, we illustrate the utility of our new resource, xQTL Serve, by using it to prioritize the cell type(s) most affected by an xQTL. We also reanalyze published genome wide association studies using an xQTL-weighted analysis approach and identify 18 new schizophrenia and 2 new bipolar susceptibility variants, which is more than double the number of loci that can be discovered with a larger blood-based expression eQTL resource.

Background In droplet-based single-cell and single-nucleus RNA-seq experiments, not all reads associated with one cell barcode originate from the encapsulated cell. Such background noise is attributed to spillage from cell-free ambient RNA or barcode swapping events. Results Here, we characterize this background noise exemplified by three scRNA-seq and two snRNA-seq replicates of mouse kidneys. For each experiment, cells from two mouse subspecies are pooled, allowing to identify cross-genotype contaminating molecules and thus profile background noise. Background noise is highly variable across replicates and cells, making up on average 3–35% of the total counts (UMIs) per cell and we find that noise levels are directly proportional to the specificity and detectability of marker genes. In search of the source of background noise, we find multiple lines of evidence that the majority of background molecules originates from ambient RNA. Finally, we use our genotype-based estimates to evaluate the performance of three methods (CellBender, DecontX, SoupX) that are designed to quantify and remove background noise. We find that CellBender provides the most precise estimates of background noise levels and also yields the highest improvement for marker gene detection. By contrast, clustering and classification of cells are fairly robust towards background noise and only small improvements can be achieved by background removal that may come at the cost of distortions in fine structure. Conclusions Our findings help to better understand the extent, sources and impact of background noise in single-cell experiments and provide guidance on how to deal with it.

Aging can lead to cognitive decline associated with neural pathology and Alzheimer's disease (AD). Here the authors scan the methylation status of CpGs across the entire genome of brain samples from aged subjects in an epigenome-wide association study (EWAS). Several loci, including ANK1, were associated with AD pathology, gene expression and AD genetic risk networks. We used a collection of 708 prospectively collected autopsied brains to assess the methylation state of the brain's DNA in relation to Alzheimer's disease (AD). We found that the level of methylation at 71 of the 415,848 interrogated CpGs was significantly associated with the burden of AD pathology, including CpGs in the ABCA7 and BIN1 regions, which harbor known AD susceptibility variants. We validated 11 of the differentially methylated regions in an independent set of 117 subjects. Furthermore, we functionally validated these CpG associations and identified the nearby genes whose RNA expression was altered in AD: ANK1 , CDH23 , DIP2A , RHBDF2 , RPL13 , SERPINF1 and SERPINF2 . Our analyses suggest that these DNA methylation changes may have a role in the onset of AD given that we observed them in presymptomatic subjects and that six of the validated genes connect to a known AD susceptibility gene network.

Single-nucleus RNA-seq (snRNA-seq) enables the interrogation of cellular states in complex tissues that are challenging to dissociate or are frozen, and opens the way to human genetics studies, clinical trials, and precise cell atlases of large organs. However, such applications are currently limited by batch effects, processing, and costs. Here, we present an approach for multiplexing snRNA-seq, using sample-barcoded antibodies to uniquely label nuclei from distinct samples. Comparing human brain cortex samples profiled with or without hashing antibodies, we demonstrate that nucleus hashing does not significantly alter recovered profiles. We develop DemuxEM, a computational tool that detects inter-sample multiplets and assigns singlets to their sample of origin, and validate its accuracy using sex-specific gene expression, species-mixing and natural genetic variation. Our approach will facilitate tissue atlases of isogenic model organisms or from multiple biopsies or longitudinal samples of one donor, and large-scale perturbation screens. Single-nucleus RNA-seq enables interrogation of complex tissues but is limited due to batch effects and processing costs. Here the authors use barcoded antibodies against the nuclear pore complex to label nuclei from distinct samples, and develop a computational tool to assign the sample of origin.

We initiated the systematic profiling of the dorsolateral prefrontal cortex obtained from a subset of autopsied individuals enrolled in the Religious Orders Study (ROS) or the Rush Memory and Aging Project (MAP), which are jointly designed prospective studies of aging and dementia with detailed, longitudinal cognitive phenotyping during life and a quantitative, structured neuropathologic examination after death. They include over 3,322 subjects. Here, we outline the first generation of data including genome-wide genotypes (n=2,090), whole genome sequencing (n=1,179), DNA methylation (n=740), chromatin immunoprecipitation with sequencing using an anti-Histone 3 Lysine 9 acetylation (H3K9Ac) antibody (n=712), RNA sequencing (n=638), and miRNA profile (n=702). Generation of other omic data including ATACseq, proteomic and metabolomics profiles is ongoing. Thanks to its prospective design and recruitment of older, non-demented individuals, these data can be repurposed to investigate a large number of syndromic and quantitative neuroscience phenotypes. The many subjects that are cognitively non-impaired at death also offer insights into the biology of the human brain in older non-impaired individuals.

To extend our understanding of the genetic basis of human immune function and dysfunction, we performed an expression quantitative trait locus (eQTL) study of purified CD4+ T cells and monocytes, representing adaptive and innate immunity, in a multi-ethnic cohort of 461 healthy individuals. Context-specific cis- and trans-eQTLs were identified, and cross-population mapping allowed, in some cases, putative functional assignment of candidate causal regulatory variants for disease-associated loci. We note an over-representation of T cell–specific eQTLs among susceptibility alleles for autoimmune diseases and of monocyte-specific eQTLs among Alzheimer's and Parkinson's disease variants. This polarization implicates specific immune cell types in these diseases and points to the need to identify the cell-autonomous effects of disease susceptibility variants.

It is difficult to determine the mechanistic consequences of context-dependent genetic variants, some of which may be related to disease (see the Perspective by Gregersen ). Two studies now report on the effects of stimulating immunological monocytes and dendritic cells with proteins that can elicit a response to bacterial or viral infection and assess the functional links between genetic variants and profiles of gene expression. M. N. Lee et al. ( 10.1126/science.1246980 ) analyzed the expression of more than 400 genes, in dendritic cells from 534 healthy subjects, which revealed how expression quantitative trait loci (eQTLs) affect gene expression within the interferon-β and the Toll-like receptor 3 and 4 pathways. Fairfax et al. ( 10.1126/science.1246949 ) performed a genome-wide analysis to show that many eQTLs affected monocyte gene expression in a stimulus- or time-specific manner. Mapping of human host-pathogen gene-by-environment interactions identifies pathogen-specific loci. [Also see Perspective by Gregersen ] Little is known about how human genetic variation affects the responses to environmental stimuli in the context of complex diseases. Experimental and computational approaches were applied to determine the effects of genetic variation on the induction of pathogen-responsive genes in human dendritic cells. We identified 121 common genetic variants associated in cis with variation in expression responses to Escherichia coli lipopolysaccharide, influenza, or interferon-β (IFN-β). We localized and validated causal variants to binding sites of pathogen-activated STAT (signal transducer and activator of transcription) and IRF (IFN-regulatory factor) transcription factors. We also identified a common variant in IRF7 that is associated in trans with type I IFN induction in response to influenza infection. Our results reveal common alleles that explain interindividual variation in pathogen sensing and provide functional annotation for genetic variants that alter susceptibility to inflammatory diseases.

Nicotinamide mononucleotide adenylyl transferase 2 (NMNAT2) is neuroprotective in numerous preclinical models of neurodegeneration. Here, we show that brain nmnat2 mRNA levels correlate positively with global cognitive function and negatively with AD pathology. In AD brains, NMNAT2 mRNA and protein levels are reduced. NMNAT2 shifts its solubility and colocalizes with aggregated Tau in AD brains, similar to chaperones, which aid in the clearance or refolding of misfolded proteins. Investigating the mechanism of this observation, we discover a novel chaperone function of NMNAT2, independent from its enzymatic activity. NMNAT2 complexes with heat shock protein 90 (HSP90) to refold aggregated protein substrates. NMNAT2's refoldase activity requires a unique C-terminal ATP site, activated in the presence of HSP90. Furthermore, deleting NMNAT2 function increases the vulnerability of cortical neurons to proteotoxic stress and excitotoxicity. Interestingly, NMNAT2 acts as a chaperone to reduce proteotoxic stress, while its enzymatic activity protects neurons from excitotoxicity. Taken together, our data indicate that NMNAT2 exerts its chaperone or enzymatic function in a context-dependent manner to maintain neuronal health.

RNA editing is a feature of RNA maturation resulting in the formation of transcripts whose sequence differs from the genome template. Brain RNA editing may be altered in Alzheimer’s disease (AD). Here, we analyzed data from 1,865 brain samples covering 9 brain regions from 1,074 unrelated subjects on a transcriptome-wide scale to identify inter-regional differences in RNA editing. We expand the list of known brain editing events by identifying 58,761 previously unreported events. We note that only a small proportion of these editing events are found at the protein level in our proteome-wide validation effort. We also identified the occurrence of editing events associated with AD dementia, neuropathological measures and longitudinal cognitive decline in: SYT11 , MCUR1 , SOD2 , ORAI2 , HSDL2 , PFKP , and GPRC5B . Thus, we present an extended reference set of brain RNA editing events, identify a subset that are found to be expressed at the protein level, and extend the narrative of transcriptomic perturbation in AD to RNA editing. Resources reporting RNA editing sites from brain tissue have been published. Here, the authors provide an atlas of RNA editing events found in the aged and Alzheimer’s disease human brain tissue resulting in changes at protein level.