An integrative systems approach identifies novel candidates in Marfan syndrome-related pathophysiology

Abstract

Marfan syndrome (MFS) is an autosomal dominant genetic disorder caused by mutations in the FBN1 gene. Although many peripheral tissues are affected, aortic complications, such as dilation, dissection and rupture, are the leading causes of MFS-related mortality. Aberrant TGF-beta signalling plays a major role in the pathophysiology of MFS. However, the contributing mechanisms are still poorly understood. Here, we aimed at identifying novel aorta-specific pathways involved in the pathophysiology of MFS. For this purpose, we employed the Fbn1 under-expressing mgR/mgR mouse model of MFS. We performed RNA-sequencing of aortic tissues of 9-week-old mgR/mgR mice compared with wild-type (WT) mice. With a false discovery rate <5%, our analysis revealed 248 genes to be differentially regulated including 20 genes previously unrelated with MFS-related pathology. Among these, we identified Igfbp2, Ccl8, Spp1, Mylk2, Mfap4, Dsp and H19. We confirmed the expression of regulated genes by quantitative real-time PCR. Pathway classification revealed transcript signatures involved in chemokine signalling, cardiac muscle contraction, dilated and hypertrophic cardiomyopathy. Furthermore, our immunoblot analysis of aortic tissues revealed altered regulation of pSmad2 signalling, Perk1/2, Igfbp2, Mfap4, Ccl8 and Mylk2 protein levels in mgR/mgR vs WT mice. Together, our integrative systems approach identified several novel factors associated with MFS-aortic-specific pathophysiology that might offer potential novel therapeutic targets for MFS.

Keywords: Chemokine signalling; Igfbp2 signalling; Marfan syndrome; Mfap4; RNA-sequencing; Spp1; TGF-beta signalling; Transcriptomics; mgR/mgR.

Figure 1

RNA‐sequencing analysis of WT vs mgR/mgR aorta. A, Verhoeff‐van Gieson staining in wild‐type (WT) vs mgR/mgR mouse. Van Gieson staining was performed on aortas isolated from wild‐type and mgR mice. Increased elastin fragmentation and breaks were observed in Marfan mice, compared to wild‐type. B, Differential expression of genes by RNA‐ sequencing analysis in WT vs mgR/mgR aortas (9 wk) animals. Heatmap depicting the Log2 FKPM values of significantly regulated genes (P < 0.05). The red colour indicates the low expression of genes and white indicates the high expression of genes. C, Comparison of our RNA‐sequencing data to published microarray (Schwill, Seppelt et al. 2013). Our comparison identified, 23 genes to be commonly regulated between both and 225 genes to be exclusively regulated in our dataset and 126 genes exclusive to Schwill, Seppelt dataset

Figure 2

Validation of up‐regulated genes from RNA‐sequencing data. A‐E, qPCRs were performed between WT vs mgR/mgR aortas for the up‐regulated genes from RNA‐sequencing data. Fold changes were calculated and Gapdh was used as normalizing control. Data were validated across n = 3 different biological replicates. Each replicate is derived from three pooled WT vs mgR tissues (11 weeks old)

Figure 3

Validation of down‐regulated genes from RNA‐sequencing data. A‐G, qPCR was performed between WT vs mgR/mgR aortas for the down‐regulated genes from RNA‐ sequencing data. Fold changes were calculated and Gapdh was used as a normalizing control. Data were validated across n = 3 or n = 2 different biological replicates. Each replicate is derived from three pooled WT vs mgR tissues (11 weeks old)

Figure 4

Protein validations of identified genes from RNA‐sequencing data by Western blots. A) pSmad2 and B) pErk1/2 protein levels were induced in mgR/mgR aortic tissues compared to WT (11 weeks old animals). Up‐regulation of C) Igfbp2, E) Ccl8 and F) Mylk2 protein levels and Down‐regulation of D) Mfap4 protein levels in mgR/mgR aortic tissues compared to WT. Protein lysates were harvested as described in methods sections. Gapdh or Hsp60 was used as a loading control