Distinct amyloid-beta and tau-associated microglia profiles in Alzheimer's disease

Alzheimer's disease (AD) is the most prevalent form of dementia and is characterized by abnormal extracellular aggregates of amyloid-beta and intraneuronal hyperphosphorylated tau tangles and neuropil threads. Microglia, the tissue-resident macrophages of the central nervous system (CNS), are important for CNS homeostasis and implicated in AD pathology. In amyloid mouse models, a phagocytic/activated microglia phenotype has been identified. How increasing levels of amyloid-beta and tau pathology affect human microglia transcriptional profiles is unknown. Here, we performed snRNAseq on 482,472 nuclei from non-demented control brains and AD brains containing only amyloid-beta plaques or both amyloid-beta plaques and tau pathology. Within the microglia population, distinct expression profiles were identified of which two were AD pathology-associated. The phagocytic/activated AD1-microglia population abundance strongly correlated with tissue amyloid-beta load and localized to amyloid-beta plaques. The AD2-microglia abundance strongly correlated with tissue phospho-tau load and these microglia were more abundant in samples with overt tau pathology. This full characterization of human disease-associated microglia phenotypes provides new insights in the pathophysiological role of microglia in AD and offers new targets for microglia-state-specific therapeutic strategies

Integrated Expression Profiles of mRNA and miRNA in Polarized Primary Murine Microglia

<div><p>Neuroinflammation contributes to many neurologic disorders including Alzheimer’s disease, multiple sclerosis, and stroke. Microglia is brain resident myeloid cells and have emerged as a key driver of the neuroinflammatory responses. MicroRNAs (miRNAs) provide a novel layer of gene regulation and play a critical role in regulating the inflammatory response of peripheral macrophages. However, little is known about the miRNA in inflammatory activation of microglia. To elucidate the role that miRNAs have on microglial phenotypes under classical (M1) or alternative (M2) activation under lipopolysaccharide (‘M1’-skewing) and interleukin-4 (‘M2a’-skewing) stimulation conditions, we performed microarray expression profiling and bioinformatics analysis of both mRNA and miRNA using primary cultured murine microglia. miR-689, miR-124, and miR-155 were the most strongly associated miRNAs predicted to mediate pro-inflammatory pathways and M1-like activation phenotype. miR-155, the most strongly up-regulated miRNA, regulates the signal transducer and activator of transcription 3 signaling pathway enabling the late phase response to M1-skewing stimulation. Reduced expression in miR-689 and miR-124 are associated with dis-inhibition of many canonical inflammatory pathways. miR-124, miR-711, miR-145 are the strongly associated miRNAs predicted to mediate anti-inflammatory pathways and M2-like activation phenotype. Reductions in miR-711 and miR-124 may regulate inflammatory signaling pathways and peroxisome proliferator-activated receptor-gamma pathway. miR-145 potentially regulate peripheral monocyte/macrophage differentiation and faciliate the M2-skewing phenotype. Overall, through combined miRNA and mRNA expression profiling and bioinformatics analysis we have identified six miRNAs and their putative roles in M1 and M2-skewing of microglial activation through different signaling pathways.</p></div

Bioinformatic correlation analysis of miRNA:mRNA interactions in microglia

<p>. (A) Method employed for miRNA:mRNA correlation analysis and miRNA potential target enrichment analysis. Briefly, Pearson’s correlation analysis was performed to identify the genes most highly correlated with select miRNA expression profiles. This new gene set was then compared with predicted miRNA targeting gene sets. Common miRNA-correlated target genes were uploaded to Ingenuity® Systems and enrichment analysis was performed to identify targeted functions, targeted pathways, targeted transcriptional networks, and targeted networks. (B) Venn-diagram analysis of representative miRNA:mRNA correlation analysis for miR-155 targets. Predicted targets of miR-155 were derived from public sources (miRanda Database, Ingenuity or TargetScan). miR-155-correlated genes were selected based on two key criteria: a fold change p<0.0001 and strong correlation with miR-155 (r>0.5 or r<–0.5). Venn-diagram shows the intersection gene set of 112 commonly predicted targets that were also strongly correlated with miR-155. (C-D) The top 15 altered transcriptional networks and the corresponding miRNA are presented. IPA-based enrichment analysis was performed on intersected genes for each miRNA to identify key transcriptional networks in the M1-skewed (C) or M2a-skewed microglia (D). Identified transcriptional networks were pooled together from all miRNA altered in the M1- (C) or M2-skewing condition (D) and then sorted by -Log(p-value). Dotted line denotes p<0.05, corresponding to –Log(p-value) > 1.30, as statistical threshold.</p

The major risk factors for Alzheimer's disease: age, sex, and genes modulate the microglia response to Aβ plaques

Sala Frigerio et al. show how microglia respond to amyloid-β, the Alzheimer's disease (AD)-causing factor. Their major response, the ARMs response, is enriched for AD risk genes, is abolished by Apoe deletion, develops faster in female mice, and is also part of normal aging. Thus, major AD risk factors converge on microglia.</p