Multi-Omics Analysis of Microglial Extracellular Vesicles From Human Alzheimer's Disease Brain Tissue Reveals Disease-Associated Signatures

Abstract

Alzheimer's disease (AD) is the most common cause of dementia, yet there is no cure or diagnostics available prior to the onset of clinical symptoms. Extracellular vesicles (EVs) are lipid bilayer-delimited particles that are released from almost all types of cell. Genome-wide association studies have linked multiple AD genetic risk factors to microglia-specific pathways. It is plausible that microglia-derived EVs may play a role in the progression of AD by contributing to the dissemination of insoluble pathogenic proteins, such as tau and Aβ. Despite the potential utility of EVs as a diagnostic tool, our knowledge of human brain EV subpopulations is limited. Here we present a method for isolating microglial CD11b-positive small EVs from cryopreserved human brain tissue, as well as an integrated multiomics analysis of microglial EVs enriched from the parietal cortex of four late-stage AD (Braak V-VI) and three age-matched normal/low pathology (NL) cases. This integrated analysis revealed 1,000 proteins, 594 lipids, and 105 miRNAs using shotgun proteomics, targeted lipidomics, and NanoString nCounter technology, respectively. The results showed a significant reduction in the abundance of homeostatic microglia markers P2RY12 and TMEM119, and increased levels of disease-associated microglia markers FTH1 and TREM2, in CD11b-positive EVs from AD brain compared to NL cases. Tau abundance was significantly higher in AD brain-derived microglial EVs. These changes were accompanied by the upregulation of synaptic and neuron-specific proteins in the AD group. Levels of free cholesterol were elevated in microglial EVs from the AD brain. Lipidomic analysis also revealed a proinflammatory lipid profile, endolysosomal dysfunction, and a significant AD-associated decrease in levels of docosahexaenoic acid (DHA)-containing polyunsaturated lipids, suggesting a potential defect in acyl-chain remodeling. Additionally, four miRNAs associated with immune and cellular senescence signaling pathways were significantly upregulated in the AD group. Our data suggest that loss of the homeostatic microglia signature in late AD stages may be accompanied by endolysosomal impairment and the release of undigested neuronal and myelin debris, including tau, through extracellular vesicles. We suggest that the analysis of microglia-derived EVs has merit for identifying novel EV-associated biomarkers and providing a framework for future larger-scale multiomics studies on patient-derived cell-type-specific EVs.

Keywords: Alzheimer’s disease; exosomes; extracellular vesicles; microglia; omics analysis.

FIGURE 1

Small EV fraction characterization and microglial EV purification. (A) Representative transmission electron microscopy (TEM) image of small EV fraction (F2) isolated from the human parietal cortex. (B) Tunable resistive pulse sensing (TRPS) analysis of the F2 fraction isolated from the human parietal cortex. (C) A representative image of immunoblot analysis of an F2 fraction using antibodies against exosomal markers (CD9, CD81, and syntenin-1) and negative control markers (GM130 and calnexin, CNX). (D) A representative image of immunoblot analysis of two immunoprecipitation (IP) samples pull-down either with antibodies against microglial marker CD11b or with corresponding isotype control antibodies (rat IgG2b). Membrane was probed with the exosomal marker CD63. (E) Immunoblotting of CD11b-IP samples and isotype control samples probed with antibodies against a microglial marker (CD11b), an exosomal marker (CD9), and tau. (F) Immunoblotting of the F2 fraction isolated from the human parietal cortex and corresponded CD11b-IP fraction with antibodies against the exosomal marker CD63 and the microglial marker TMEM119. The sample volume was equal between CD63 and TMEM119 immunoblots. (G) Relative abundances of microglial markers, TMEM119 and P2RY12, in F2 (n = 6) and CD11b-IP samples (n = 7) as indicated by LC-MS/MS (**p < 0.001; ***p < 0.0001).

FIGURE 2

Proteomic analysis of microglial EVs from normal/low pathology and late-stage AD cases. (A) Venn diagram representing microglial proteins differentially detected in NL and AD groups. (B) Volcano plot showing a degree of differential expression of proteins in NL and AD groups. Vertical red dotted lines separate proteins, which are two or more times less abundant in AD (far left segment) and two or more times more abundant in AD (far right segment). Horizontal red dotted line separates the top part of the plot containing dots representing proteins whose abundances are significantly different between NL and AD groups (p < 0.05) and the bottom part (no significant changes). Proteins that are significantly different between AD and NL groups are color-coded: two or more times more abundant in AD are presented in red, two or more times less abundant in green. (C) Heat map of proteins significantly up- and downregulated in AD compared to the NL group across seven evaluated human cases. (D) Immunoblotting of CD11b-IP samples with antibodies against ApoE and TREM2. Representative images are in the upper section and the composite data are in the lower section (*p < 0.05). (E) Gene ontology enrichment bioinformatic analysis of proteins two or more times less abundant in AD compared to NL. (F) Gene ontology enrichment bioinformatic analysis of proteins two or more times more abundant in AD compared to NL.

FIGURE 3

miRNA transcriptomic analysis of microglial EVs from normal/low pathology and late-stage AD cases. (A) Volcano plot showing a degree of differential expression of miRNAs in NL and AD groups. Vertical red dotted lines separate miRNA, which are 1.5 or more times less abundant in AD (far left segment) and 1.5 or more times more abundant in AD (far right segment). Horizontal red dotted line separates the top section of the plot containing dots representing proteins whose abundance is significantly different between NL and AD groups (*p < 0.05). MicroRNAs, which are significantly different between AD and NL groups, are color-coded: 1.5 or more times more abundant in AD are presented in red, 1.5 or more times less abundant are in green. (B) Gene ontology enrichment bioinformatic analysis of miRNAs significantly more abundant in AD compared to NL.

FIGURE 4

Lipidomic analysis of microglial EVs from normal/low pathology and late-stage AD cases. (A) Relative quantification 34 lipid classes and 593 individual lipid species in microglial EVs. Lipids are quantified as mol% total lipid by normalizing the molar amount of each lipid species to the summed total moles of all lipid species in each sample. The inset panels show lower abundance species on the expanded y-axis. Abbreviations are free cholesterol (FC), cholesteryl ester (CE), acyl carnitine (AC), monoacylglycerol (MG), diacylglycerol (DG), triacylglycerol (TG), ceramide (Cer), sphingomyelin (SM), monohexosylceramide (MhCer), sulfatides (Sulf), lactosylceramide (LacCer), monosialodihexosylganglioside (GM3), globotriaosylceramide (GB3), phosphatidic acid (PA), phosphatidylcholine (PC), ether phosphatidylcholine (PCe), phosphatidylethanolamine (PE), plasmalogen phosphatidylethanolamine (Pep), phosphatidylserine (PS), phosphatidylinositol (PI), phosphatidylglycerol (PG), bis(monoacylglycerol)phosphate (BMP), acyl phosphatidylglycerol (AcylPG), lysophosphatidylcholine (LPC), ether lysophosphatidylcholine (LPCe), lysophosphatidylethanolamine (LPE), plasmalogen lysophosphatidylethanolamine (LPEp), lysophosphatidylinositol (LPI), lysophosphatidylserine (LPS), N-Acyl phosphatidylethanolamine (NAPE), N-acyl phosphatidylserine (NAPS), and N-acyl serine (NSer). Data are presented as mean mol% with error bars showing mean ± S.E. FC is significantly increased shown in the primary panel (p < 0.01). (B) PE species were detected using mass spectrometry and are shown using relative quantification as mol%. PE 38:0 (p < 0.05); PE 38:1 (p < 0.01). (C) Most abundant LPE [LPE20:4 (p < 0.05)] and (D) NAPE [NAPE 16:0/18:0/20:4 (p < 0.05)] lipid species are shown to significantly differ between LN- and AD-derived microglia EV. (E) PA40:6 lipid species is decreased in microglia-derived EV from the AD brain (AD) compared to control (LN) (p < 0.0001), while no other PA species are significantly affected. (F) The most abundant PS species, PS40:6 species, is decreased in EV derived from the AD brain (AD) compared to control (LN) (p < 0.001) while no other PS species are significantly altered. (G) The most abundant BMP 36:2 (p < 0.0001) and (H) MhCer d18:1/24:1 (p < 0.01) lipid species are increased in AD-derived microglia EV. All data are presented as mean mol% with error bars showing mean ± S.E.