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Systems level analysis of systemic sclerosis shows a network of immune and profibrotic pathways connected with genetic polymorphisms.

Mahoney JM, Taroni J, Martyanov V, Wood TA, Greene CS, Pioli PA, Hinchcliff ME, Whitfield ML - PLoS Comput. Biol. (2015)

Bottom Line: Here we identify the genes consistently associated with the intrinsic subsets across three independent cohorts, show the relationship between these genes using a gene-gene interaction network, and place the genetic risk loci in the context of the intrinsic subsets.We created a gene-gene interaction network of the conserved molecular features across the intrinsic subsets and analyzed their connections with SSc-associated genetic polymorphisms.The network also shows connections between these subset-specific genes and 30 SSc-associated polymorphic genes including STAT4, BLK, IRF7, NOTCH4, PLAUR, CSK, IRAK1, and several human leukocyte antigen (HLA) genes.

View Article: PubMed Central - PubMed

Affiliation: Department of Genetics, Geisel School of Medicine at Dartmouth, Hannover, New Hampshire, United States of America.

ABSTRACT
Systemic sclerosis (SSc) is a rare systemic autoimmune disease characterized by skin and organ fibrosis. The pathogenesis of SSc and its progression are poorly understood. The SSc intrinsic gene expression subsets (inflammatory, fibroproliferative, normal-like, and limited) are observed in multiple clinical cohorts of patients with SSc. Analysis of longitudinal skin biopsies suggests that a patient's subset assignment is stable over 6-12 months. Genetically, SSc is multi-factorial with many genetic risk loci for SSc generally and for specific clinical manifestations. Here we identify the genes consistently associated with the intrinsic subsets across three independent cohorts, show the relationship between these genes using a gene-gene interaction network, and place the genetic risk loci in the context of the intrinsic subsets. To identify gene expression modules common to three independent datasets from three different clinical centers, we developed a consensus clustering procedure based on mutual information of partitions, an information theory concept, and performed a meta-analysis of these genome-wide gene expression datasets. We created a gene-gene interaction network of the conserved molecular features across the intrinsic subsets and analyzed their connections with SSc-associated genetic polymorphisms. The network is composed of distinct, but interconnected, components related to interferon activation, M2 macrophages, adaptive immunity, extracellular matrix remodeling, and cell proliferation. The network shows extensive connections between the inflammatory- and fibroproliferative-specific genes. The network also shows connections between these subset-specific genes and 30 SSc-associated polymorphic genes including STAT4, BLK, IRF7, NOTCH4, PLAUR, CSK, IRAK1, and several human leukocyte antigen (HLA) genes. Our analyses suggest that the gene expression changes underlying the SSc subsets may be long-lived, but mechanistically interconnected and related to a patients underlying genetic risk.

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Bridges between components of the network.Several genes bridge the component subnetworks of the molecular network. PLAUR is a gene that contains SSc-associated polymorphisms that forms a bridge between the interferon subnetwork and TGFβ/ECM subnetwork. The gene RAC2 is a bridge between the interferon and M2 macrophage subnetworks. The genes LCP2 and CXCR4 are bridges between the M2 macrophage subnetwork and the adaptive immunity subnetwork. There are also several paths through GRB10 to ADAP2 between the M2 macrophage subnetwork and the adaptive immunity subnetwork. The genes CD14 and THY1 (CD90) are bridges between the M2 macrophage subnetwork and the TGFβ/ECM subnetwork. The genes IRAK1 and PXK are bridges between the TGFβ/ECM subnetwork and the cell proliferation subnetwork.
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pcbi-1004005-g006: Bridges between components of the network.Several genes bridge the component subnetworks of the molecular network. PLAUR is a gene that contains SSc-associated polymorphisms that forms a bridge between the interferon subnetwork and TGFβ/ECM subnetwork. The gene RAC2 is a bridge between the interferon and M2 macrophage subnetworks. The genes LCP2 and CXCR4 are bridges between the M2 macrophage subnetwork and the adaptive immunity subnetwork. There are also several paths through GRB10 to ADAP2 between the M2 macrophage subnetwork and the adaptive immunity subnetwork. The genes CD14 and THY1 (CD90) are bridges between the M2 macrophage subnetwork and the TGFβ/ECM subnetwork. The genes IRAK1 and PXK are bridges between the TGFβ/ECM subnetwork and the cell proliferation subnetwork.

Mentions: In addition to containing discrete subnetworks, the molecular network also shows genes that bridge the subnetworks (Fig. 6). These genes are of particular interest because they have predicted connections between multiple, distinct subnetworks. The primary reason for using CC3 and CC9 simultaneously as queries to IMP was to identify possible molecular connections between the core molecular processes of the inflammatory and fibroproliferative intrinsic subsets. The bridge genes live at the interfaces between the subnetworks that constitute these core molecular processes.


Systems level analysis of systemic sclerosis shows a network of immune and profibrotic pathways connected with genetic polymorphisms.

Mahoney JM, Taroni J, Martyanov V, Wood TA, Greene CS, Pioli PA, Hinchcliff ME, Whitfield ML - PLoS Comput. Biol. (2015)

Bridges between components of the network.Several genes bridge the component subnetworks of the molecular network. PLAUR is a gene that contains SSc-associated polymorphisms that forms a bridge between the interferon subnetwork and TGFβ/ECM subnetwork. The gene RAC2 is a bridge between the interferon and M2 macrophage subnetworks. The genes LCP2 and CXCR4 are bridges between the M2 macrophage subnetwork and the adaptive immunity subnetwork. There are also several paths through GRB10 to ADAP2 between the M2 macrophage subnetwork and the adaptive immunity subnetwork. The genes CD14 and THY1 (CD90) are bridges between the M2 macrophage subnetwork and the TGFβ/ECM subnetwork. The genes IRAK1 and PXK are bridges between the TGFβ/ECM subnetwork and the cell proliferation subnetwork.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4288710&req=5

pcbi-1004005-g006: Bridges between components of the network.Several genes bridge the component subnetworks of the molecular network. PLAUR is a gene that contains SSc-associated polymorphisms that forms a bridge between the interferon subnetwork and TGFβ/ECM subnetwork. The gene RAC2 is a bridge between the interferon and M2 macrophage subnetworks. The genes LCP2 and CXCR4 are bridges between the M2 macrophage subnetwork and the adaptive immunity subnetwork. There are also several paths through GRB10 to ADAP2 between the M2 macrophage subnetwork and the adaptive immunity subnetwork. The genes CD14 and THY1 (CD90) are bridges between the M2 macrophage subnetwork and the TGFβ/ECM subnetwork. The genes IRAK1 and PXK are bridges between the TGFβ/ECM subnetwork and the cell proliferation subnetwork.
Mentions: In addition to containing discrete subnetworks, the molecular network also shows genes that bridge the subnetworks (Fig. 6). These genes are of particular interest because they have predicted connections between multiple, distinct subnetworks. The primary reason for using CC3 and CC9 simultaneously as queries to IMP was to identify possible molecular connections between the core molecular processes of the inflammatory and fibroproliferative intrinsic subsets. The bridge genes live at the interfaces between the subnetworks that constitute these core molecular processes.

Bottom Line: Here we identify the genes consistently associated with the intrinsic subsets across three independent cohorts, show the relationship between these genes using a gene-gene interaction network, and place the genetic risk loci in the context of the intrinsic subsets.We created a gene-gene interaction network of the conserved molecular features across the intrinsic subsets and analyzed their connections with SSc-associated genetic polymorphisms.The network also shows connections between these subset-specific genes and 30 SSc-associated polymorphic genes including STAT4, BLK, IRF7, NOTCH4, PLAUR, CSK, IRAK1, and several human leukocyte antigen (HLA) genes.

View Article: PubMed Central - PubMed

Affiliation: Department of Genetics, Geisel School of Medicine at Dartmouth, Hannover, New Hampshire, United States of America.

ABSTRACT
Systemic sclerosis (SSc) is a rare systemic autoimmune disease characterized by skin and organ fibrosis. The pathogenesis of SSc and its progression are poorly understood. The SSc intrinsic gene expression subsets (inflammatory, fibroproliferative, normal-like, and limited) are observed in multiple clinical cohorts of patients with SSc. Analysis of longitudinal skin biopsies suggests that a patient's subset assignment is stable over 6-12 months. Genetically, SSc is multi-factorial with many genetic risk loci for SSc generally and for specific clinical manifestations. Here we identify the genes consistently associated with the intrinsic subsets across three independent cohorts, show the relationship between these genes using a gene-gene interaction network, and place the genetic risk loci in the context of the intrinsic subsets. To identify gene expression modules common to three independent datasets from three different clinical centers, we developed a consensus clustering procedure based on mutual information of partitions, an information theory concept, and performed a meta-analysis of these genome-wide gene expression datasets. We created a gene-gene interaction network of the conserved molecular features across the intrinsic subsets and analyzed their connections with SSc-associated genetic polymorphisms. The network is composed of distinct, but interconnected, components related to interferon activation, M2 macrophages, adaptive immunity, extracellular matrix remodeling, and cell proliferation. The network shows extensive connections between the inflammatory- and fibroproliferative-specific genes. The network also shows connections between these subset-specific genes and 30 SSc-associated polymorphic genes including STAT4, BLK, IRF7, NOTCH4, PLAUR, CSK, IRAK1, and several human leukocyte antigen (HLA) genes. Our analyses suggest that the gene expression changes underlying the SSc subsets may be long-lived, but mechanistically interconnected and related to a patients underlying genetic risk.

Show MeSH
Related in: MedlinePlus