Systemic Inflammation Causes Microglial Dysfunction With a Vascular AD phenotype

Abstract

Background: Studies in rodents and humans have indicated that inflammation outside CNS (systemic inflammation) affects brain homeostasis contributing to neurodevelopmental disorders. Itis becoming increasingly evident that such early insults may also belinked to neurodegenerative diseases like late-onset Alzheimer's disease (AD). Importantly, lifestyle and stress, such as viral or bacterial infection causing chronic inflammation, may contribute to neurodegenerative dementia. Systemic inflammatory response triggers a cascade of neuroinflammatory responses, altering brain transcriptome, cell death characteristic of AD, and vascular dementia. Our study aimed to assess the temporal evolution of the pathological impact of systemic inflammation evoked by prenatal and early postnatal peripheral exposure of viral mimetic Polyinosinic:polycytidylic acid (PolyI:C) and compare the hippocampal transcriptomic changes with the profiles of human post-mortem AD and vascular dementia brain specimens.

Methods: We have engineered the PolyI:C sterile infection model in wildtype C57BL6 mice to achieve chronic low-grade systemic inflammation. We have conducted a cross-sectional analysis of aging PolyI:C and Saline control mice (3 months, 6 months, 9 months, and 16 months), taking the hippocampus as a reference brain region, and compared the brain aging phenotype to AD progression in humans with mild AD, severe AD, and Controls (CTL), in parallel to Vascular dementia (VaD) patients' specimens.

Results: We found that PolyI:C mice display both peripheral and central inflammation with a peak at 6 months, associated with memory deficits. The hippocampus is characterized by a pronounced and progressive tauopathy. In PolyI:C brains, microglia undergo aging-dependent morphological shifts progressively adopting a phagocytic phenotype. Transcriptomic analysis reveals a profound change in gene expression throughout aging, with a peak in differential expression at 9 months. We show that the proinflammatory marker Lcn2 is one of the genes with the strongest upregulation in PolyI:C mice upon aging. Validation in brains from patients with increasing severity of AD and VaD shows the reproducibility of some gene targets in vascular dementia specimens as compared to AD ones.

Conclusions: The PolyI:C model of sterile infection demonstrates that peripheral chronic inflammation causes progressive tau hyperphosphorylation, changes in microglia morphology, astrogliosis and gene reprogramming reflecting increased neuroinflammation, vascular remodeling, and the loss of neuronal functionality seen to some extent in human AD and Vascular dementia suggesting early immune insults could be crucial in neurodegenerative diseases.

Keywords: Brain aging; Inflammation; Microglia; PolyI:C; Sporadic Alzheimer's disease; Vascular dementia.

Fig. 1

The neuroinflammatory evolution in aging PolyI:C mice: (A) Timeline of the experimental procedure and PolyI:C injections. (B) qPCR quantification of pro-inflammatory cytokines (IL-6, IL-1beta, INF-gamma) in the hippocampus after the PolyI:C treatment. Transcript analysis for (C) neuronal (GRIN), (D) microglia (Iba1) and (E) astroglial (GFAP) markers; represented as mean ± SEM, n = 4–5 mice per age and treatment. *p < 0.05, **p < 0.005, #p = 0.07. Statistical significance based on two-way ANOVA with Bonferroni post hoc analysis. (F) Correlation matrix indicates the associations between time series of Grin1, Iba1, GFAP with the examined cytokines. Highlighted squares with significant correlation. GD = gestational day, BD = birth day.

Fig. 2

The Effect of PolyI:C on p-tau accumulation in the hippocampus: (A) Immunoblots of hippocampal lysate from PP and NN mice at 3, 6, 9 and 16 months, for p-tau, tau, GFAP, Synaptophysin. β-Actin was used as housekeeping control. (B,D) Relative quantification of Tau, GFAP and Synaptophysin represented in normalized optical density. (C,E) Percentage of relative changes of these proteins compared to the saline treated controls. Representative immunostaining for (F) p-tau (9 months) and (G) p-tau, Aβ_1-16 and GFAP at 16 months age group. Insert shows a GFAP positive process with internalized p-tau aggregates. Scale bar in F is 45 μm, G is 20 μm. Values represented as mean ± SEM, n = 4–5 mice per age and treatment. *p < 0.05, **p < 0.005, ***p < 0.0005 #p = 0.07. Statistical significance based on two-way ANOVA with Bonferroni post hoc analysis.

Fig. 3

Amyloid immunostaining in the hippocampus and spatial memory deficits. (A) Double immunolabeling for Aβ_1-16 and GFAP shows internalization of amyloid in GFAP + glia cells (stars) in NN and PP mice at 16 months and depositions of amyloid in vessels (white arrows) in PP mice. (B) Representative immunostaining of S97 and 3A1 anti-β-Amyloid antibodies in the hippocampus of aged 16 months PP, NN controls and APP PS1 positive control, showing no signs of plaque formation after PolyI:C treatment (C) Effect of PolyI:C treatment on memory task assessed with Spontaneous alternation indicate a significant impairment in the percent of spontaneous alternation entry in PP mice compared from 6 to 16 months as compared to NN (n = 7–10 mice per treatment and age). (D) Regardless of treatment, 9mo and 16mo old mice showed less total number of arm entries. Values in bar charts and line graph are represented as mean ± SEM. *p < 0.05, **p < 0.005, two-way ANOVA followed by Benjamini Krieger and Yekutieli post hoc analyses. Scale bar in A = 20 μm and B = 10 μm. Abbreviations: NN = prenatal & postnatal saline injected controls, PP = prenatal and postnatal PolyI:C treated mice.

Fig. 4

Longitudinal changes in hippocampal microglia: (A) Immunofluorescence staining for Iba1 staining in the PolyI:C treated mice. (B) Dynamic changes in microglia soma size, perimeter and circularity were quantified in Saline(NN) and PolyI:C (PP) mice in different age groups. (n = 3–4 mice per group & condition, data points come from 4 equidistant planes and at least 5 ROI`s/animal,*p < 0.05, two-way anova followed by Fisher's LSD test) (C) Bar chart representing the effect of treatment and aging on the average endpoints maximum branch length per cell (n = 3 mice per age group and condition, *p < 0.05, two-way ANOVA, followed by Benjamini Krieger and Yekutieli post hoc analyses, #p = 0.09) (D) Example of fractal analysis of microglia from the hippocampus of PolyI:C and saline treated 16 months aged mice. 63x single cell fractal analysis indicate the surface area (E) and perimeter (F) were decreased in PP mice, in contrast to the span ratio (G) showed a higher trend. PP mice showed a significant decrease in cell circularity (H) and fractal dimension (I), n = 45 cells from 3 mice per group and condition, mean ± SEM. #p = 0.07,*p < 0.05, **p < 0.005 Student's t-test. Scale bar, A = 20 μm.

Fig. 5

Bulk transcriptomics analysis of hippocampus in the aging PolyI:C. Gene expression changes after the prenatal and early postnatal immune challenge. Volcano plot with log2-fold change (X-axis) and -log10 p-value (Y-axis) at different age groups (A) 3 months (B) 6months (C) 9 months and (D) 16 months in PP versus NN controls. Genes with log2 fold changes >0.5 are shown in green. Significantly regulated genes are shown in red (log2 fold change >0.5, p < 0.05, left downregulated and right upregulated). Genes with insignificant log2 fold changes <0.5 are shown in black [controls (NN) n = 3/age, PolyI:C (PP) n = 3/age. (E) Venn diagram indicating the number of uniquely and commonly affected genes in the aging hippocampus following prenatal and early postnatal PolyI:C (PP) treatment. Few common genes along with their Log2 Fold changes either (F) downregulated or (G) upregulated were plotted across staging. Transcript validation analysis for (H)Egr2 and Kcnj2 and (I)Plin4 and Lcn2, *p<0.05, **p<0.005, two-way ANOVA with Benjamini Krieger and Yekutieli post hoc analyses, [controls (NN), n = 5/age, PolyI:C (PP) n = 4–5/age] (J) Spearman correlation matrix for mRNA levels (Log₂FC) with highlighted significant association from 9 to 16 months among the differentially expressed cell-type markers (GFAP, Iba1 and Grin1) and Egr2, Kcnj2, Plin4 and Lcn2 between PolyI:C and saline.

Fig. 6

Effect of PolyI:C on the hippocampal Lcn-2 & lipid droplet (LD) density. (A) Representative Lcn-2 stained confocal images of saline and PolyI:C treated mice in 9 months and 16 months aged PP mice. Larger aggregates of Lcn-2 (insert) visible at the 16 months PolyI:C exposed mice. (B) Quantification of % stained area indicates increased Lcn2 expression in the hippocampal CA3 field, *p < 0.05, two-way ANOVA followed with Holm-Sidak`s multiple comparison (n = 4–6 mice for 9 and 16-months groups/treatment). (C) Nile red positive lipid droplet staining (violet) across aging in NN & PP mice. Inserts showing aggregated lipid droplets (D) Representative triple fluorescence labeling with Nile Red, Iba1 (teal) and NF200 (grey) shows overlap between the different marker localized lipid droplets in Iba1 positive cells. Arrows indicating NileRed⁺/Iba1⁺ cells. (E) Bar chart representing the lipid droplet (LD) density, mean size and % stained area per ROI measured. Data are represented as mean ± SEM (n = 3–4 mice per groups/treatment). *p < 0.05, **p < 0.005, two-way ANOVA, Fischer LSD. Scale bar A = 20 μm, C,E = 10 μm.

Fig. 7

Target transcripts validation in the human brain specimen of patients with AD and VaD. Bar plots with Jitter showing the fold changes (FC) of the DEGs (A–F) in moderate AD and severe AD entorhinal cortices as compared to healthy controls (CTRL) and (H–M) in hippocampal sections from VaD as compared to healthy controls (CTRL). (A and H) FC of cell-type specific markers for astroglia (GFAP), microglia (Iba1) and neurons (MAP2). (B and I) FC of glucose metabolism markers, Glpr2 and Ide. (C and J) FC of plasticity markers, Egr2 and Kcnj2. (D and K) FC of cell signaling markers, c-fos, c-Jun and Notch1. (E and L) FC of inflammatory and metabolic markers, Lcn2 and Plin4. (F and M). FC of vascular markers, Angptl4, Cyp1b1 and Klf4. (G and N) Correlation matrix of the selected biomarkers in the two study cohorts. Data are represented as Geometric mean of fold change ± Geometric SEM relative to healthy controls. *p < 0.05, #p = 0.054 based on one-way ANOVA/Bonferroni post hoc test correction. AD = Alzheimer's disease and VaD = vascular dementia.