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. 2023 Sep 8;13(1):14800.
doi: 10.1038/s41598-023-41897-6.

Lipid metabolism transcriptomics of murine microglia in Alzheimer's disease and neuroinflammation

Daniel C Shippy  1 , Tyler K Ulland  2
Affiliations

Lipid metabolism transcriptomics of murine microglia in Alzheimer's disease and neuroinflammation

Daniel C Shippy et al. Sci Rep. .

Abstract

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the accumulation of amyloid-β (Aβ) plaques followed by intracellular neurofibrillary tangles (NFTs) composed of hyperphosphorylated tau. An unrestrained immune response by microglia, the resident cells of the central nervous system (CNS), leads to neuroinflammation which can amplify AD pathology. AD pathology is also driven by metabolic dysfunction with strong correlations between dementia and metabolic disorders such as diabetes, hypercholesterolemia, and hypertriglyceridemia. Since elevated cholesterol and triglyceride levels appear to be a major risk factor for developing AD, we investigated the lipid metabolism transcriptome in an AD versus non-AD state using RNA-sequencing (RNA-seq) and microarray datasets from N9 cells and murine microglia. We identified 52 differentially expressed genes (DEG) linked to lipid metabolism in LPS-stimulated N9 microglia versus unstimulated control cells using RNA-seq, 86 lipid metabolism DEG in 5XFAD versus wild-type mice by microarray, with 16 DEG common between both datasets. Functional enrichment and network analyses identified several biological processes and molecular functions, such as cholesterol homeostasis, insulin signaling, and triglyceride metabolism. Furthermore, therapeutic drugs targeting lipid metabolism DEG found in our study were identified. Focusing on drugs that target genes associated with lipid metabolism and neuroinflammation could provide new targets for AD drug development.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Differentially expressed lipid metabolism genes in AD. (A) Scatter plot of lipid metabolism DEG (log2FC > 0.5, FDR-adjusted P-value < 0.05) by RNA-seq in N9 microglia stimulated with LPS (1 µg/ml) for 6 h versus unstimulated control cells. (B) Scatter plot of lipid metabolism DEG (log2FC > 0.5, P < 0.05) by microarray in microglia isolated from the brains of 5XFAD mice versus wild-type mice (8 months old). For both scatter plots, up-regulated genes are shown in red and down-regulated genes are shown in green. Data are graphed as log2FC versus − log10 (P-value). (C) Venn diagram demonstrating overlap in lipid metabolism DEG between the N9 and mouse microglia datasets.
Figure 2
Figure 2
N9 microglia GO enrichment analysis. Biological function analyses for the N9 microglial lipid metabolism DEG was performed using DAVID. Analyses were performed for biological process (BP) (A), cellular component (CC) (B), and molecular function (MF) (C). Pathways are shown in descending order based on − log10 FDR. The number of genes associated with each GO term is shown above each bar. Only GO terms with a gene count ≥ 5 and FDR < 0.05 were considered significant.
Figure 3
Figure 3
Mouse microglia GO enrichment analysis. Biological function analyses for the mouse microglial lipid metabolism DEG was performed using DAVID. Analyses were performed for biological process (BP) (A), cellular component (CC) (B), and molecular function (MF) (C). Pathways are shown in descending order based on − log10 FDR. The number of genes associated with each GO term is shown above each bar. Only GO terms with a gene count ≥ 5 and FDR < 0.05 were considered significant.
Figure 4
Figure 4
KEGG pathway enrichment analysis. KEGG pathway analysis was performed on the lipid metabolism DEG from the N9 microglia RNA-seq (A) and mouse microglia microarray (B) using DAVID. Pathways are shown in descending order based on − log10 FDR. The number of genes associated with each pathway is shown above each bar. Only pathways with a gene count ≥ 5 and FDR < 0.05 were considered significant.
Figure 5
Figure 5
PPI analysis using STRING. STRING analysis was performed on the N9 (A) and mouse (B) microglial lipid metabolism DEG. For the analysis, text mining, experiments, and databases were chosen for active interaction sources, and a high value of 0.700 was selected as the minimum required interaction score. Line colors represent known interactions from curated databases (blue), experimentation (purple) and text mining (yellow). The proteins for which there were no connections to be mapped are not shown.
Figure 6
Figure 6
Gene–drug interactions. Interactions between therapeutic drugs and the 16 lipid metabolism DEG common to both datasets. Genes identified with drug interactions are shown and the number of drugs associated with each gene is shown above each bar.
Figure 7
Figure 7
Cybb expression network analysis. Gene constellations for Cybb were created using ImmGen. (A) Positive expression correlation of genes to Cybb. (B) Negative expression correlation of genes to Cybb.
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