Fig. 5: TBI leads to elevated expression of disease-associated genes when the brain possesses pre-existing lymphatic deficits. | Nature Communications

Fig. 5: TBI leads to elevated expression of disease-associated genes when the brain possesses pre-existing lymphatic deficits.

From: Meningeal lymphatic dysfunction exacerbates traumatic brain injury pathogenesis

Fig. 5

Mice were subjected to an injection of Visudyne or vehicle i.c.m. and 15 min later a red laser was directed at 5 spots along the sinuses through the skull. After a week of rest, mice received TBI or a sham procedure. One week after injury, RNA was isolated from homogenized brains. Bulk RNA sequencing was performed on these four experimental groups with four individual mice per group. a Principal component (PC) analysis showing clustering of samples. b Volcano plots illustrate the number of significantly differentially expressed genes (FDR < 0.1). Blue data points represent significantly downregulated genes and red data points represent significantly upregulated genes. c, d Gene set enrichment analysis using the (c) Reactome database and (d) Biocarta pathway database shows enrichment of immune-related pathways with differentially expressed genes between TBI mice with pre-existing lymphatic dysfunction compared to mice with TBI alone. e Circos plot depicting differentially expressed genes in TBI mice with pre-existing lymphatic dysfunction compared to mice with TBI alone (FDR < 0.1) associated with neurodegenerative or psychiatric diseases. The proportion of the circle’s circumference allocated to each disease represents the number of genes associated with that disease that are also differentially expressed in the Not Ablated + TBI vs. Ablated + TBI comparison. The lines connecting genes within the circle indicate which genes were shared amongst disease signatures. f Scatterplot showing the adjusted P value and the expression changes of genes shown in (e). padj, adjusted p-value; pval, p-value. wpi week(s) post injury. FDR and P values were calculated with DEseq2 using the Wald test for significance following fitting to a negative binomial linear model and the Benjamini–Hochberg procedure to control for false discoveries.

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