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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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Related in: MedlinePlus

Hubs in the inflammatory and ECM components of the network.The putative MRSS biomarker gene IFI44 is a hub of the type 1 interferon subnetwork. AIF1, which contains SSc-associated polymorphisms and is related to M2 macrophage polarization, is a hub of the M2 macrophage network. FBN1, which contains SSc-associated polymorphisms in some populations and is a key component of ECM that regulates matrix stiffness, is a hub of the TGFβ/ECM network. The tyrosine kinase gene LYN is associated with B cell activation and mediating self-tolerance and is a hub in the adaptive immunity subnetwork.
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pcbi-1004005-g005: Hubs in the inflammatory and ECM components of the network.The putative MRSS biomarker gene IFI44 is a hub of the type 1 interferon subnetwork. AIF1, which contains SSc-associated polymorphisms and is related to M2 macrophage polarization, is a hub of the M2 macrophage network. FBN1, which contains SSc-associated polymorphisms in some populations and is a key component of ECM that regulates matrix stiffness, is a hub of the TGFβ/ECM network. The tyrosine kinase gene LYN is associated with B cell activation and mediating self-tolerance and is a hub in the adaptive immunity subnetwork.

Mentions: Interferon-induced protein 44 (IFI44) is a hub of the interferon subnetwork. It has conserved high expression across all three of our cohorts in the inflammatory subset and is one of the most highly connected genes in the interferon subnetwork (Fig. 5, top right). IFI44 is predicted to have co-expression interactions with several other interferon-inducible and interferon-regulating genes, including IFI16, IRF7, IFITM2, ISG20, GBP1, and TRIM22.


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)

Hubs in the inflammatory and ECM components of the network.The putative MRSS biomarker gene IFI44 is a hub of the type 1 interferon subnetwork. AIF1, which contains SSc-associated polymorphisms and is related to M2 macrophage polarization, is a hub of the M2 macrophage network. FBN1, which contains SSc-associated polymorphisms in some populations and is a key component of ECM that regulates matrix stiffness, is a hub of the TGFβ/ECM network. The tyrosine kinase gene LYN is associated with B cell activation and mediating self-tolerance and is a hub in the adaptive immunity subnetwork.
© Copyright Policy
Related In: Results  -  Collection

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

pcbi-1004005-g005: Hubs in the inflammatory and ECM components of the network.The putative MRSS biomarker gene IFI44 is a hub of the type 1 interferon subnetwork. AIF1, which contains SSc-associated polymorphisms and is related to M2 macrophage polarization, is a hub of the M2 macrophage network. FBN1, which contains SSc-associated polymorphisms in some populations and is a key component of ECM that regulates matrix stiffness, is a hub of the TGFβ/ECM network. The tyrosine kinase gene LYN is associated with B cell activation and mediating self-tolerance and is a hub in the adaptive immunity subnetwork.
Mentions: Interferon-induced protein 44 (IFI44) is a hub of the interferon subnetwork. It has conserved high expression across all three of our cohorts in the inflammatory subset and is one of the most highly connected genes in the interferon subnetwork (Fig. 5, top right). IFI44 is predicted to have co-expression interactions with several other interferon-inducible and interferon-regulating genes, including IFI16, IRF7, IFITM2, ISG20, GBP1, and TRIM22.

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