Microglia states and nomenclature: A field at its crossroads

Neuron, Journal Year: 2022, Volume and Issue: 110(21), P. 3458 - 3483

Published: Nov. 1, 2022

Language: Английский

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Molecular characterization of selectively vulnerable neurons in Alzheimer’s disease

Nature Neuroscience, Journal Year: 2021, Volume and Issue: 24(2), P. 276 - 287

Published: Jan. 11, 2021

Language: Английский

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Crosstalk Between Astrocytes and Microglia: An Overview

Frontiers in Immunology, Journal Year: 2020, Volume and Issue: 11

Published: July 16, 2020

Based on discoveries enabled by new technologies and analyzed using novel computational tools, neuroscience can be re-conceived in terms of information exchange dense networks intercellular connections rather than the context individual populations, such as glia or neurons.. Cross-talk between neurons microglia astrocytes are has been addressed, however, manner which non-neuronal cells communicate interact remains less well understood. We review this intriguing crosstalk among CNS cells, focusing how it contributes to brain development two neurodegenerative diseases: Alzheimer disease GRN-FTLD most prevalent tumor, astrocytoma. The goal studying these communications is promote our ability combat incurable neurological disorders.

Language: Английский

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The neurobiology of long COVID

Neuron, Journal Year: 2022, Volume and Issue: 110(21), P. 3484 - 3496

Published: Oct. 7, 2022

Persistent neurological and neuropsychiatric symptoms affect a substantial fraction of people after COVID-19 represent major component the post-acute syndrome, also known as long COVID. Here, we review what is understood about pathobiology impact on CNS discuss possible neurobiological underpinnings cognitive affecting survivors. We propose chief mechanisms that may contribute to this emerging health crisis.

Language: Английский

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Microglia in Alzheimer's disease at single-cell level. Are there common patterns in humans and mice?

The Journal of Experimental Medicine, Journal Year: 2021, Volume and Issue: 218(9)

Published: July 22, 2021

Alzheimer's disease (AD) is characterized by extracellular aggregates of amyloid β peptides, intraneuronal tau aggregates, and neuronal death. This pathology triggers activation microglia. Because variants genes expressed in microglia correlate with AD risk, microglial response to plausibly impacts course. In mouse models, single-cell RNA sequencing (scRNA-seq) analyses delineated this as progressive conversion homeostatic into disease-associated (DAM); additional reactive populations have been reported other models neurodegeneration neuroinflammation. We review all these signatures, highlighting four fundamental patterns: DAM, IFN-microglia, MHC-II microglia, proliferating propose that are either just one or a combination, depending on the clustering strategy applied model. further single-nucleus (snRNA-seq) data from human specimens discuss reasons for parallels discrepancies between transcriptional profiles. Finally, we outline future directions delineating impact pathogenesis.

Language: Английский

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Cholesterol and matrisome pathways dysregulated in astrocytes and microglia

Cell, Journal Year: 2022, Volume and Issue: 185(13), P. 2213 - 2233.e25

Published: June 1, 2022

Language: Английский

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Novel Alzheimer risk genes determine the microglia response to amyloid‐β but not to TAU pathology

EMBO Molecular Medicine, Journal Year: 2020, Volume and Issue: 12(3)

Published: Jan. 17, 2020

Article17 January 2020Open Access Transparent process Novel Alzheimer risk genes determine the microglia response to amyloid-β but not TAU pathology Annerieke Sierksma orcid.org/0000-0001-9233-972X VIB Center for Brain & Disease Research, Leuven, Belgium Laboratory Research of Neurodegenerative Diseases, Department Neurosciences, Leuven Institute (LBI), KU (University Leuven), Search more papers by this author Ashley Lu Renzo Mancuso orcid.org/0000-0002-7046-3348 Nicola Fattorelli orcid.org/0000-0001-5564-8179 Thrupp Evgenia Salta Jesus Zoco orcid.org/0000-0003-1164-4306 David Blum orcid.org/0000-0001-5691-431X INSERM, CHU Lille, LabEx DISTALZ, UMR-S 1172, Tauopathies, Université France Luc Buée Bart De Strooper Corresponding Author [email protected] orcid.org/0000-0001-5455-5819 UK Dementia Institute, University College London, Mark Fiers orcid.org/0000-0001-5694-2409 Information Sierksma1,2,‡, Lu1,2,‡, Mancuso1,2, Fattorelli1,2, Thrupp1,2, Salta1,2, Zoco1,2, Blum3, Buée3, *,1,2,4,‡ and *,1,2,‡ 1VIB 2Laboratory 3INSERM, 4UK ‡These authors contributed equally work as first senior *Corresponding author. Tel: +32 4957 71044; E-mail: 4944 95150; EMBO Mol Med (2020)12:e10606https://doi.org/10.15252/emmm.201910606 PDFDownload PDF article text main figures. Peer ReviewDownload a summary editorial decision including letters, reviewer comments responses feedback. ToolsAdd favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures Info Abstract Polygenic scores have identified that genetic variants without genome-wide significance still add developing Alzheimer's disease (AD). Whether how subthreshold loci translate into relevant pathways is unknown. We investigate here involvement AD in transcriptional two mouse models: APPswe/PS1L166P Thy-TAU22. A unique gene expression module, highly enriched genes, specifically responsive Aβ pathology. identify module 7 established (APOE, CLU, INPP5D, CD33, PLCG2, SPI1, FCER1G) 11 GWAS below threshold (GPC2, TREML2, SYK, GRN, SLC2A5, SAMSN1, PYDC1, HEXB, RRBP1, LYN, BLNK), become significantly upregulated when exposed Aβ. Single sequencing confirms Aβ, TAU, induces marked changes microglia, increased proportions activated microglia. conclude functionally translates different pathway pathology, placing downstream amyloid upstream Synopsis It unknown (AD) manifests itself at molecular cellular level brain. Analysis TAUtg an APPtg models show mainly reflected are among transcriptomic APPtg/Amyloid plaques forming mice massive deregulation with aging, increasing neuroinflammatory while TAUtg/tangle display downregulation neuronal genes. Many above genome wide co-regulated large involved neuroinflammation. 18 prioritized, which all expressed may regulate their function (in red synopsis figure). 15 many adopt phenotype facing than Introduction Genetic background strongly determines sporadic (Gatz et al, 2006). Unlike APOE4 polymorphism 42 other loci, thousands SNPs associated do reach (Efthymiou Goate, 2017; Marioni 2018; Verheijen Sleegers, 2018). (PRSs) incorporate contributions these variations relate (Purcell 2009). PRSs currently prediction accuracy 84%, albeit major proportion can be attributed APOE status alone (Escott-Price 2017). Two crucial questions arise from myriad studies: (i) Are linked (Aβ) or (ii) they converge within single pathway, define parallel lead AD? Although it remains challenging causally link affected we expect least part implicated association studies (GWAS) affect brain (De Karran, 2016; Efthymiou Such model integrates parts hypothesis complex genetics AD, will coherent view on pathogenesis AD. Profiling postmortem tissue only provides insights advanced stages cannot delineate cause–consequence relationships, required develop mechanistic (Zhang 2013). Transgenic hand partially recapitulate frontotemporal dementia (FTD) phenotypes, provide detailed functional initial steps disease, high relevance preventative therapeutic interventions (Zahs Ashe, 2010). What lacking until now, however, integration information data obtained human. Doing so help whether sub-significant This would increase confidence truly indicate play role. Here, perform profiling hippocampus after exposure early (4 months age; 4M) mature (10-11M). use (APPtg) Thy-TAU22 (TAUtg) mice, both expressing transgene Thy1.2 promotor (Radde 2006; Schindowski The biochemical insults mimicked animals reflect morphological hallmarks (SAD) familial cases (FAD). Therefore, FAD useful assess demonstrate despite similar robust cognitive severe age-dependent deregulation, milder over time stable phenotype. uniquely coordinated deregulated multicellular network functions Tau observe alterations biology. strong neuroinflammation demonstrating (ARM; 57%) homeostatic (20%) APPtg-11M whereas phenotypic shifts were much less pronounced TAUtg-11M mice. Our evidence microglial promotes candidate future research. Results At 4M age, cognitively intact mild levels 10M overlapping profiles hippocampus-dependent mnemonic deficits substantial (see Fig 1A; Radde Lo RNA-seq was performed (TG) respective wild-type (WT) littermates, n = 12 per group 96 total, yielding average 7.7 million reads sample 1B). Bulk good alteration upon onset progression allows us uncover co-regulation beyond individual cell types. Figure 1. Enrichment A. Visualization load TAUwt, TAUtg, 9M age. Immunofluorescent staining X34 (a fluorescent derivative Congo Red; magenta), Iba1 (microglia; green), TO-PRO-3 (nuclei; blue) has been pseudocolored. Scale bar 100 μm. B. Experimental design mRNA using experimental group. C. Explanation 2 × linear model, where those cells labeled 1 compared 0. In age comparison, 10-month-old (10M) 4-month-old (4M) genotype transgenic age*genotype transcripts differentially TG groups. D. Based al (2018), various sets created cut-off P-values indicated x-axis (number each set written gray). assessed statistical comparisons (A*G: age*genotype, Gen: genotype), enrichment analysis (GSEA, Subramanian 2005). Colors represent Benjamini–Yekutieli-adjusted P-value enrichment; blank means no significant enrichment. Download figure PowerPoint found (Fig 1C) employed effects genotype, interaction. comparison identifies change between strain (i.e., WT 10M, analyzing strains separately; see 2A). shows differences 2B). interaction, finally, assesses aging 2C). study thus reflects manifesting critical points: initially signs occur, later on, manifest accompanying deficits. 2. Changes exacerbate miceLog2 fold (LFC) (x-axis) (y-axis) differential analysis. Upregulated right (TAUtg mice) upper (APPtg graph; downregulated left lower graph. Colored dots (Benjamini–Yekutieli-adjusted (Padj) < 0.05) (green dots), (yellow (red dots). Spearman correlation ranking either most up- combined score LFC Padj signed log10(P-value), sign determined LFC). Genes i.e., versus independently genotype. Thus, positive due TG, interaction comparing TG-10M groups 1C). Depicts 314 Marioni-based P 0.001 onto LFC/LFC plot (panel C). Green changed. wondered GWAS-based included variants, 5 10e-8 studies, well contribute predictions through polygenic inheritance 2015, examined multiple such taken combines Biobank AD-by-proxy IGAP database confers based proximity (thus referred noticing assumptions). Using arbitrary Bonferroni-adjusted (Pmar) cut-offs decreasing association, size 1D Appendix Table S1). PRS demonstrated up 0.5 improve predictive power decided limit our Pmar 0.05, already 1,799 (GSEA; 1D) size, ranging 92 (Pmar 5e-6) 5e-2), consistently, (Padj 1e-250) changing ("APPtg A*G" 1D), smallest (n 5e-06) contains microglia-expressed e.g., Treml2, Inpp5d, Gal3st4, 2D Dataset EV1). enhance clustering To effect detail 2A–C caused independent transgene) practically identical (Spearman R +0.95, 1.3e-29, 95% interval (CI) +0.91 +0.97; When only, similarity becomes rather moderate (R +0.50, 1.1e-19, CI +0.41 +0.58; 2B) slightly enhanced +0.67, 1e-106, +0.63 +0.71; ways, very pathologies causing divergent reactions. APP/PSEN1 causes prominent (287 total) dots, 219, 76%) [log2 (LFC): +0.07 +5.00, 0.05]. component added age*genotype), even [623 mRNAs 78%), LFC: +0.12 +2.98, 0.05], 175 downregulate (LFC: −0.67 −0.08, 0.05; often responses, Tyrobp (LFC (G): +1.19, (A*G): +1.53), Cst7 G: A*G: +2.62), Itgax +3.22, +2.24). These strong, 32-fold. Indeed, specific types (Zeisel 2015), verify 80% microglia-specific predominantly 2D). appears likely source, persistent 2C) follow response. As discuss below, origin being explained microgliosis 2006), also consequence states (Keren-Shaul Krasemann Sala Frigerio 2019). Click expand figure. EV1. glial loadZ-score distribution type-specific defined Zeisel (2015) SynaptomeDB (Pirooznia 2012). Boxplots: center line, median; box limits, 25th–75th quartiles; whiskers, 1.5× interquartile range. Empirical (Pbonf) shift z-score Materials Methods). ***Pbonf 0.001, **Pbonf 0.01, *Pbonf 0.05. markedly fewer little aggravation time. (TAUwt TAUtg), 47 +0.06 +1.52; 77 −1.30 −0.05, 2B, yellow Only 9 +0.25 +0.60, 2C, dots) model. majority (62%) TAUwt decreased overlap (C1qa, C1qc, Tyrobp, Ctss, Irf8, Mpeg1, Cst7, Rab3il1) astroglial (Gfap) origin. (much milder) TAUtg. With exception 2.08), upregulation indeed modest (average 8 others: 0.38) (max 2.98; 0.70). Similarly, demonstrates astrocytic older ages, loss synaptic Overall, molecular, pathobiological, fundamentally exhibiting phenotypes drives exacerbating inflammatory response, related functions. Most importantly, transcriptionally active accumulating Next, unbiased weighted co-expression (WGCNA; Zhang Horvath, 2005; Langfelder 2008) separately cluster modules. total 63 modules (Appendix Figs S2 S3). GSEA generated 3A S1), largest (e.g., enrich 4 APPtg- TAUtg-based (Turquoise, Blue, However, taking smaller), persistently APPtg-Blue 3A). 4,236) 62% [age*genotype, expected chance (log2 odds ratio (LOR): 2.90, 1.54e-158)]. assume integrated important stress large, APPTg-Blue (1e-250 0.01). generally module. 3. represents present Gene Fisher's exact test (2018) WGCNA-derived −log10 P-value) Numbers x-axis: black cut-off; gray set. Log2 analysis, assessing Color code dots/numbers: 15,824); 4,236); green 493); 9); 9). Z-score (***Pbonf 0.001) Ontology (GO) depicts −log10(FDR-adjusted multiplied (ES), line −log10(0.049)*(ES 1). E. "top 18" prioritized finding intersection 4,236), 314), 798), SuperExactTest (Wang 2015). italics

Language: Английский

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Microglia Phenotypes in Aging and Neurodegenerative Diseases

Cells, Journal Year: 2022, Volume and Issue: 11(13), P. 2091 - 2091

Published: June 30, 2022

Neuroinflammation is a hallmark of many neurodegenerative diseases (NDs) and plays fundamental role in mediating the onset progression disease. Microglia, which function as first-line immune guardians central nervous system (CNS), are drivers neuroinflammation. Numerous human postmortem studies vivo imaging analyses have shown chronically activated microglia patients with various acute chronic neuropathological diseases. While microglial activation common feature NDs, exact pathological states complex often contradictory. However, there consensus that play biphasic conditions, detrimental protective phenotypes, overall response different phenotypes depends on nature duration inflammatory insult, well stage disease development. This review provides comprehensive overview current research responses health, aging, special emphasis heterogeneous phenotypic such hemorrhagic stroke (HS), Alzheimer's (AD), Parkinson's (PD). The primary focus translational preclinical animal models bulk/single-cell transcriptome samples. Additionally, this covers key receptors signaling pathways potential therapeutic targets to regulate during aging NDs. age-, sex-, species-specific differences will be briefly reviewed.

Language: Английский

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Microglia in the Neuroinflammatory Pathogenesis of Alzheimer’s Disease and Related Therapeutic Targets

Frontiers in Immunology, Journal Year: 2022, Volume and Issue: 13

Published: April 26, 2022

Alzheimer's disease (AD) is the most prevalent neurodegenerative worldwide, characterized by progressive neuron degeneration or loss due to excessive accumulation of β-amyloid (Aβ) peptides, formation neurofibrillary tangles (NFTs), and hyperphosphorylated tau. The treatment AD has been only partially successful as majority pharmacotherapies on market may alleviate some symptoms. In occurrence AD, increasing attention paid neurodegeneration, while resident glial cells, like microglia are also observed. Microglia, a kind crucial cells associated with innate immune response, functions double-edge sword role in CNS. They exert beneficial detrimental influence adjacent neurons through secretion both pro-inflammatory cytokines well neurotrophic factors. addition, their endocytosis debris toxic protein Aβ tau ensures homeostasis neuronal microenvironment. this review, we will systematically summarize recent research regarding roles pathology latest microglia-associated therapeutic targets mainly including genes, anti-inflammatory genes phagocytosis at length, which contradictory controversial warrant further be investigated.

Language: Английский

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Human microglial state dynamics in Alzheimer’s disease progression

Cell, Journal Year: 2023, Volume and Issue: 186(20), P. 4386 - 4403.e29

Published: Sept. 1, 2023

Altered microglial states affect neuroinflammation, neurodegeneration, and disease but remain poorly understood. Here, we report 194,000 single-nucleus transcriptomes epigenomes across 443 human subjects diverse Alzheimer's (AD) pathological phenotypes. We annotate 12 transcriptional states, including AD-dysregulated homeostatic, inflammatory, lipid-processing states. identify 1,542 AD-differentially-expressed genes, both microglia-state-specific disease-stage-specific alterations. By integrating epigenomic, transcriptomic, motif information, infer upstream regulators of cell gene-regulatory networks, enhancer-gene links, transcription-factor-driven state transitions. demonstrate that ectopic expression our predicted homeostatic-state activators induces homeostatic features in iPSC-derived microglia-like cells, while inhibiting inflammation can block inflammatory progression. Lastly, pinpoint the AD-risk genes differential their during AD Overall, provide insights underlying state-specific AD-stage-specific alterations at unprecedented resolution.

Language: Английский

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