Autoimmunity and autoinflammation: A systems view on signaling pathway dysregulation profiles.

Arsen Arakelyan, Lilit Nersisyan, David Poghosyan, Lusine Khondkaryan, Anna Hakobyan, Henry Löffler-Wirth, Evie Melanitou, Hans Binder
Author Information
  1. Arsen Arakelyan: Bioinformatics Group, Institute of Molecular Biology, National Academy of Sciences RA, Yerevan, Armenia. ORCID
  2. Lilit Nersisyan: Bioinformatics Group, Institute of Molecular Biology, National Academy of Sciences RA, Yerevan, Armenia.
  3. David Poghosyan: Group of Immune Response Regulation, Institute of Molecular Biology, National Academy of Sciences RA, Yerevan, Armenia.
  4. Lusine Khondkaryan: Group of Immune Response Regulation, Institute of Molecular Biology, National Academy of Sciences RA, Yerevan, Armenia.
  5. Anna Hakobyan: Bioinformatics Group, Institute of Molecular Biology, National Academy of Sciences RA, Yerevan, Armenia.
  6. Henry Löffler-Wirth: Interdisciplinary Centre for Bioinformatics, University of Leipzig, Leipzig, Germany.
  7. Evie Melanitou: Department of Parasitology and Insect Vectors, Institut Pasteur, Paris, France.
  8. Hans Binder: Interdisciplinary Centre for Bioinformatics, University of Leipzig, Leipzig, Germany.

Abstract

INTRODUCTION: Autoinflammatory and autoimmune disorders are characterized by aberrant changes in innate and adaptive immunity that may lead from an initial inflammatory state to an organ specific damage. These disorders possess heterogeneity in terms of affected organs and clinical phenotypes. However, despite the differences in etiology and phenotypic variations, they share genetic associations, treatment responses and clinical manifestations. The mechanisms involved in their initiation and development remain poorly understood, however the existence of some clear similarities between autoimmune and autoinflammatory disorders indicates variable degrees of interaction between immune-related mechanisms.
METHODS: Our study aims at contributing to a holistic, pathway-centered view on the inflammatory condition of autoimmune and autoinflammatory diseases. We have evaluated similarities and specificities of pathway activity changes in twelve autoimmune and autoinflammatory disorders by performing meta-analysis of publicly available gene expression datasets generated from peripheral blood mononuclear cells, using a bioinformatics pipeline that integrates Self Organizing Maps and Pathway Signal Flow algorithms along with KEGG pathway topologies.
RESULTS AND CONCLUSIONS: The results reveal that clinically divergent disease groups share common pathway perturbation profiles. We identified pathways, similarly perturbed in all the studied diseases, such as PI3K-Akt, Toll-like receptor, and NF-kappa B signaling, that serve as integrators of signals guiding immune cell polarization, migration, growth, survival and differentiation. Further, two clusters of diseases were identified based on specifically dysregulated pathways: one gathering mostly autoimmune and the other mainly autoinflammatory diseases. Cluster separation was driven not only by apparent involvement of pathways implicated in adaptive immunity in one case, and inflammation in the other, but also by processes not explicitly related to immune response, but rather representing various events related to the formation of specific pathophysiological environment. Thus, our data suggest that while all of the studied diseases are affected by activation of common inflammatory processes, disease-specific variations in their relative balance are also identified.

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MeSH Term

Autoimmunity
Humans
Inflammation
Systems Biology

Word Cloud

Created with Highcharts 10.0.0autoimmunediseasesdisordersautoinflammatorypathwayinflammatoryidentifiedchangesadaptiveimmunityspecificaffectedclinicalvariationssharemechanismssimilaritiesviewcommonprofilespathwaysstudiedsignalingimmuneonealsoprocessesrelatedINTRODUCTION:AutoinflammatorycharacterizedaberrantinnatemayleadinitialstateorgandamagepossessheterogeneitytermsorgansphenotypesHoweverdespitedifferencesetiologyphenotypicgeneticassociationstreatmentresponsesmanifestationsinvolvedinitiationdevelopmentremainpoorlyunderstoodhoweverexistenceclearindicatesvariabledegreesinteractionimmune-relatedMETHODS:studyaimscontributingholisticpathway-centeredconditionevaluatedspecificitiesactivitytwelveperformingmeta-analysispubliclyavailablegeneexpressiondatasetsgeneratedperipheralbloodmononuclearcellsusingbioinformaticspipelineintegratesSelfOrganizingMapsPathwaySignalFlowalgorithmsalongKEGGtopologiesRESULTSANDCONCLUSIONS:resultsrevealclinicallydivergentdiseasegroupsperturbationsimilarlyperturbedPI3K-AktToll-likereceptorNF-kappaBserveintegratorssignalsguidingcellpolarizationmigrationgrowthsurvivaldifferentiationtwoclustersbasedspecificallydysregulatedpathways:gatheringmostlymainlyClusterseparationdrivenapparentinvolvementimplicatedcaseinflammationexplicitlyresponseratherrepresentingvariouseventsformationpathophysiologicalenvironmentThusdatasuggestactivationdisease-specificrelativebalanceAutoimmunityautoinflammation:systemsdysregulation

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