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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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Model of interactions among the components of the network.The molecular network of Fig. 4 is densely interconnected, implicating many possible interactions between the core molecular processes (interferon activation, M2 macrophage activation, adaptive immunity, ECM remodeling, and cell proliferation). Stepping back from the granular detail of single genes, we see a system of distinct parts through which SSc could be initiated and maintained. Among these are paths of particular interest. The interferon subnetwork and the M2 macrophage subnetwork are connected by RAC2. The M2 macrophage subnetwork in turn is connected to the ECM subnetwork through paths through CD14 and THY1. Suggesting macrophages may influence or drive ECM abnormalities in skin. The interferon subnetwork and the ECM subnetwork are connected through paths containing the pleiotropic and polymorphic gene PLAUR. The M2 macrophage subnetwork is connected to the adaptive immunity subnetwork through several distinct sets of paths through the genes GRB10, LCP2, and CXCR4. The ECM subnetwork is connected to the cell proliferation cluster through TGFβ pathway genes and paths containing the polymorphic genes IRAK1 and PXK, which suggests that ECM remodeling modulates cell proliferation through the TGFβ pathway. The interferon node may negatively regulate proliferation via the ERK/MAPK pathway resulting in the general mutual exclusivity of the inflammatory and fibroproliferative subsets. Thus we see a set of interconnected, balancing feedback loops that can enforce subset homeostasis, but also allow for patients to transition between the subsets, possibly in response to therapy.
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pcbi-1004005-g007: Model of interactions among the components of the network.The molecular network of Fig. 4 is densely interconnected, implicating many possible interactions between the core molecular processes (interferon activation, M2 macrophage activation, adaptive immunity, ECM remodeling, and cell proliferation). Stepping back from the granular detail of single genes, we see a system of distinct parts through which SSc could be initiated and maintained. Among these are paths of particular interest. The interferon subnetwork and the M2 macrophage subnetwork are connected by RAC2. The M2 macrophage subnetwork in turn is connected to the ECM subnetwork through paths through CD14 and THY1. Suggesting macrophages may influence or drive ECM abnormalities in skin. The interferon subnetwork and the ECM subnetwork are connected through paths containing the pleiotropic and polymorphic gene PLAUR. The M2 macrophage subnetwork is connected to the adaptive immunity subnetwork through several distinct sets of paths through the genes GRB10, LCP2, and CXCR4. The ECM subnetwork is connected to the cell proliferation cluster through TGFβ pathway genes and paths containing the polymorphic genes IRAK1 and PXK, which suggests that ECM remodeling modulates cell proliferation through the TGFβ pathway. The interferon node may negatively regulate proliferation via the ERK/MAPK pathway resulting in the general mutual exclusivity of the inflammatory and fibroproliferative subsets. Thus we see a set of interconnected, balancing feedback loops that can enforce subset homeostasis, but also allow for patients to transition between the subsets, possibly in response to therapy.

Mentions: The finding that most SSc-associated polymorphisms are associated with immune system mediators suggests that the initial events in SSc are likely to be immune-regulated and to involve interferon activation (Fig. 7). The immune response in SSc likely differs from a normal response because of predisposing genetic variants in these and associated genes. This may lead to the secondary recruitment of macrophages via RAS-RAC signaling (Fig. 7).


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)

Model of interactions among the components of the network.The molecular network of Fig. 4 is densely interconnected, implicating many possible interactions between the core molecular processes (interferon activation, M2 macrophage activation, adaptive immunity, ECM remodeling, and cell proliferation). Stepping back from the granular detail of single genes, we see a system of distinct parts through which SSc could be initiated and maintained. Among these are paths of particular interest. The interferon subnetwork and the M2 macrophage subnetwork are connected by RAC2. The M2 macrophage subnetwork in turn is connected to the ECM subnetwork through paths through CD14 and THY1. Suggesting macrophages may influence or drive ECM abnormalities in skin. The interferon subnetwork and the ECM subnetwork are connected through paths containing the pleiotropic and polymorphic gene PLAUR. The M2 macrophage subnetwork is connected to the adaptive immunity subnetwork through several distinct sets of paths through the genes GRB10, LCP2, and CXCR4. The ECM subnetwork is connected to the cell proliferation cluster through TGFβ pathway genes and paths containing the polymorphic genes IRAK1 and PXK, which suggests that ECM remodeling modulates cell proliferation through the TGFβ pathway. The interferon node may negatively regulate proliferation via the ERK/MAPK pathway resulting in the general mutual exclusivity of the inflammatory and fibroproliferative subsets. Thus we see a set of interconnected, balancing feedback loops that can enforce subset homeostasis, but also allow for patients to transition between the subsets, possibly in response to therapy.
© Copyright Policy
Related In: Results  -  Collection

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

pcbi-1004005-g007: Model of interactions among the components of the network.The molecular network of Fig. 4 is densely interconnected, implicating many possible interactions between the core molecular processes (interferon activation, M2 macrophage activation, adaptive immunity, ECM remodeling, and cell proliferation). Stepping back from the granular detail of single genes, we see a system of distinct parts through which SSc could be initiated and maintained. Among these are paths of particular interest. The interferon subnetwork and the M2 macrophage subnetwork are connected by RAC2. The M2 macrophage subnetwork in turn is connected to the ECM subnetwork through paths through CD14 and THY1. Suggesting macrophages may influence or drive ECM abnormalities in skin. The interferon subnetwork and the ECM subnetwork are connected through paths containing the pleiotropic and polymorphic gene PLAUR. The M2 macrophage subnetwork is connected to the adaptive immunity subnetwork through several distinct sets of paths through the genes GRB10, LCP2, and CXCR4. The ECM subnetwork is connected to the cell proliferation cluster through TGFβ pathway genes and paths containing the polymorphic genes IRAK1 and PXK, which suggests that ECM remodeling modulates cell proliferation through the TGFβ pathway. The interferon node may negatively regulate proliferation via the ERK/MAPK pathway resulting in the general mutual exclusivity of the inflammatory and fibroproliferative subsets. Thus we see a set of interconnected, balancing feedback loops that can enforce subset homeostasis, but also allow for patients to transition between the subsets, possibly in response to therapy.
Mentions: The finding that most SSc-associated polymorphisms are associated with immune system mediators suggests that the initial events in SSc are likely to be immune-regulated and to involve interferon activation (Fig. 7). The immune response in SSc likely differs from a normal response because of predisposing genetic variants in these and associated genes. This may lead to the secondary recruitment of macrophages via RAS-RAC signaling (Fig. 7).

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