Microglia-mediated neuroinflammation is hypothesized to contribute to disease progression in neurodegenerative diseases such as Alzheimer's Disease (AD). Microglia demonstrate heterogeneous states in health and disease, with proposed beneficial, harmful, and disease specific subtypes. Defining the spectrum of microglia phenotypes is an important step in rational design of neuroinflammation modulating therapies. To facilitate improved phenotype resolution and group comparisons based on disease state we performed single-nucleus RNA-seq on more than 120,000 microglia nuclei from AD and control dorsolateral prefrontal cortex. We identify clusters of microglia enriched for biological pathways implicating defined myeloid roles. We detected several previously unrecognized microglia populations in human AD brain, including three internalization and trafficking subtypes that were heterogeneous in their metabolic and inflammatory signatures. One of these endolysosomal subtypes is larger in AD individuals and was uniquely enriched for genes involved in nucleic acid detection and activation of interferon signaling. This inflammatory endolysosomal cluster also differentially regulated expression of genes associated with AD risk by genome wide association studies. We also identified a cluster of microglia with upregulated cell cycle and DNA repair genes that is proportionately larger in control individuals. Within cluster comparisons demonstrate that in AD brain, homeostatic microglia subpopulations upregulate inflammatory gene expression. These results highlight the heterogenous nature of the microglia response to AD pathology and will inform efforts to target specific subtypes of microglia in the development of novel AD therapies.
Background Microglia‐mediated neuroinflammation is hypothesized to contribute to disease progression in neurodegenerative diseases such as Alzheimer’s Disease (AD). Microglia subtypes are complex, with beneficial and harmful phenotypes. Understanding the gene expression networks which define the spectrum of microglia phenotypes is critical to identifying specific targets for neuroinflammation modulating therapies. Method Our study utilized post‐mortem brain tissue from 22 total (7 male) participants; 12 (3 male) had significant AD neuropathic change. Nuclei isolated from prefrontal cortex were sorted for the myeloid marker PU.1 using fluorescence activated nucleus sorting (FANS). The FANS approach yields larger numbers of nuclei annotated as microglia with high quality sequence from each individual. We performed single‐nucleus RNA‐seq using the 10X Genomics Chromium platform. Results We isolated more than 120,000 microglia nuclei, facilitating group comparisons based on disease state. Unbiased clustering revealed 10 microglia clusters and improved resolution of microglia heterogeneity compared to standard single‐cell approaches. We identify clusters of microglia enriched for biological pathways implicating defined myeloid roles including interferon‐stimulated, endo/lysosomal, neurodegenerative with a “disease‐associated microglia” (DAM) signature, as well as a metabolically active and autophagic cluster. Interestingly, the cluster proportionately enriched for AD individuals’ nuclei is not the DAM cluster but instead one of the clusters in which endo/lysosomal genes are highly upregulated. Furthermore, many of the genes in known AD risk loci are strongly differentially regulated in this AD associated cluster. We also identify a cluster of microglia that is proportionately enriched for control samples with upregulated cell cycle and proliferation genes. Trajectory analysis suggests that the paths AD and control nuclei take from unactivated “homeostatic” to various phenotypic states are also distinct. Conclusion Using human AD tissue collected with uniform protocols we characterize the transcriptomic profiles of microglia subtypes in human brain. By enriching for myeloid cells prior to analysis we can resolve microglia subtypes revealing the diversity of microglia which are “inflammatory” as well as other microglia subtypes responding with induction of metabolic and lysosomal pathways. Our data identifies subtypes of microglia that are unique to AD and control individuals. These results support the possibility of pharmacological targeting of specific subtypes of microglia to alter AD progression.
BackgroundMicroglia‐mediated neuroinflammation contributes to disease progression in Alzheimer’s Disease (AD). Microglia demonstrate heterogeneous states with proposed beneficial, harmful, and disease‐specific subtypes. Defining the spectrum of microglia phenotypes is crucially important to the design of neuroinflammation‐modulating therapies.MethodWe performed single‐nucleus RNA‐seq on over 120,000 microglia nuclei isolated from dorsolateral prefrontal cortices collected from 12 AD and 10 controls. Nuclei were sorted for PU.1 expression using fluorescence activated nucleus sorting.ResultsWe detected several microglia clusters that expressed features of “activation” as well as three previously unrecognized microglia transcriptomic subpopulations. These newly described subpopulations are defined by predominant endolysosomal gene expression patterns heterogeneous for metabolic and inflammatory signatures. One endolysosomal subtype is more abundant in AD individuals and uniquely enriched for transcripts involved in nucleic acid detection and interferon signaling. This population is distinct from a classic inflammatory subpopulation also present in our cohort, which upregulates NFKB, TLR and interferon related pathways but does not share the endolysosomal signature. Network analysis revealed subtype specific enrichment of IRF3 and IRF5 regulomes. AD individuals also exhibited increased expression of unfolded protein response and inflammatory genes in homeostatic microglia subpopulations.ConclusionWe demonstrate significant heterogeneity in human brain microglia subtypes including identifying multiple endolysosomal subpopulations. Like neuroinflammation, alterations in the endolysosomal system have been identified as a key component of AD pathology; however, how endolysosomal dysfunction contributes to AD progression remains unresolved. Our study is the first to identify a subpopulation of microglia in human AD brain correlating endolysosomal activity and interferon pathway induction supporting a relationship between these two pathways in AD pathogenesis. These results highlight the heterogenous nature of the microglia response to AD pathology and inform efforts to target specific subtypes of microglia in the development of novel AD therapies.
Background Single nucleus RNA sequencing (snRNA‐seq) has the potential to improve our understanding of the cellular‐specific drivers of sporadic Alzheimer’s disease. In this study we re‐analyze published snRNA‐seq data from post‐mortem dorsolateral prefrontal cortex tissue from 48 participants in the Religious Order Study and Memory and Aging Project (ROS/MAP) cohorts (Mathys et al. 2019) and snRNA‐seq data from prefrontal cortex tissue from 9 participants across the Adult Changes in Thought (ACT), University of Washington Alzheimer’s Disease Research Center (UW‐ADRC), and Seattle Longitudinal Study (SLS) cohorts. Method All snRNA‐seq data were normalized using scran, with normalized counts pre‐processed in Monocle 3. Pseudotime lineages were learned separately for male and female patients for each cell subtype with Monocle3. Genes with non‐zero counts in fewer than 10 cells in a subtype were discarded. Result We reidentified the ROS/MAP disease‐associated microglia subtype (Mic1) from Mathys et al. 2019 in the ACT, UW‐ADRC, and SLS data as determined by Fisher’s exact test overlap of subtype specific gene expression markers (p.adjusted<10−16). Furthermore, we identify a trajectory of cellular state (pseudotime) within the Mic1 population that is disease associated (p.adjusted ≤ 3.4 × 10−11 in females, and p.adjusted ≤ 4.8 × 10−4 in males) in the Mathys et al. data. In female samples in both studies we observed that APOE expression has a positive association with Mic1 pseudotime, which we do not see in males. In males we see MEF2C expression was negatively associated with Mic1 pseudotime. Lastly, we see both activation of similar Mic1 pseudotime expression patterns in a subpopulation of oligodendroglial cells, as well as a loss of oligodendroglial cells in diseased patients. Conclusion We provide increasing evidence implicating a specific microglial subpopulation in the etiology of Alzheimer’s disease. Furthermore, we see that this population has heterogeneity in expression of key Alzheimer’s disease risk genes as a function of sex, and that we can define genes that are specific to this microglial subtype lineage for further functional investigation. Finally, we also see evidence of a similar disease‐associated expression signature in oligodendroglial cells, suggesting potentially an interaction between the disease associated microglia populations and oligodendrocytes in diseased patients that warrants further functional investigation.
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