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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.

SUBMITTER: Bhushan R

PROVIDER: S-EPMC6433740 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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

Bhushan Raghu R Altinbas Lukas L Jäger Marten M Zaradzki Marcin M Lehmann Daniel D Timmermann Bernd B Clayton Nicholas P NP Zhu Yunxiang Y Kallenbach Klaus K Kararigas Georgios G Robinson Peter N PN

Journal of cellular and molecular medicine 20190124 4

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 o ...[more]

PMID: 30677223

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Project description:Obesity is a multi-factorial health problem in which genetic factors play an important role. Limited results have been obtained in single-gene studies using either genomic or transcriptomic data. RNA sequencing technology has shown its potential in gaining accurate knowledge about the transcriptome, and may reveal novel genes affecting complex diseases. Integration of genomic and transcriptomic variation (expression quantitative trait loci [eQTL] mapping) has identified causal variants that affect complex diseases. We integrated transcriptomic data from adipose tissue and genomic data from a porcine model to investigate the mechanisms involved in obesity using a systems genetics approach.Using a selective gene expression profiling approach, we selected 36 animals based on a previously created genomic Obesity Index for RNA sequencing of subcutaneous adipose tissue. Differential expression analysis was performed using the Obesity Index as a continuous variable in a linear model. eQTL mapping was then performed to integrate 60 K porcine SNP chip data with the RNA sequencing data. Results were restricted based on genome-wide significant single nucleotide polymorphisms, detected differentially expressed genes, and previously detected co-expressed gene modules. Further data integration was performed by detecting co-expression patterns among eQTLs and integration with protein data.Differential expression analysis of RNA sequencing data revealed 458 differentially expressed genes. The eQTL mapping resulted in 987 cis-eQTLs and 73 trans-eQTLs (false discovery rate?<?0.05), of which the cis-eQTLs were associated with metabolic pathways. We reduced the eQTL search space by focusing on differentially expressed and co-expressed genes and disease-associated single nucleotide polymorphisms to detect obesity-related genes and pathways. Building a co-expression network using eQTLs resulted in the detection of a module strongly associated with lipid pathways. Furthermore, we detected several obesity candidate genes, for example, ENPP1, CTSL, and ABHD12B.To our knowledge, this is the first study to perform an integrated genomics and transcriptomics (eQTL) study using, and modeling, genomic and subcutaneous adipose tissue RNA sequencing data on obesity in a porcine model. We detected several pathways and potential causal genes for obesity. Further validation and investigation may reveal their exact function and association with obesity.

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

Publications

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

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