Multi-omic landscape of Rheumatoid Arthritis: re-evaluation of drug adverse effects

Objective: To provide a frame to estimate the systemic impact (side/adverse events) of (novel) therapeutic targets by taking into consideration drugs potential on the numerous districts involved in rheumatoid arthritis (RA) from the inflammatory and immune response to the gut-intestinal (GI) microbi...

Full description

Bibliographic Details
Main Authors: Paolo eTieri, XiaoYuan eZhou, Lisha eZhu, Christine eNardini
Format: Article
Language:English
Published: Frontiers Media S.A. 2014-11-01
Series:Frontiers in Cell and Developmental Biology
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fcell.2014.00059/full
id doaj-6a2ad9dbca4e478fa3998eca6213b058
record_format Article
spelling doaj-6a2ad9dbca4e478fa3998eca6213b0582020-11-24T22:29:36ZengFrontiers Media S.A.Frontiers in Cell and Developmental Biology2296-634X2014-11-01210.3389/fcell.2014.00059108484Multi-omic landscape of Rheumatoid Arthritis: re-evaluation of drug adverse effectsPaolo eTieri0Paolo eTieri1XiaoYuan eZhou2Lisha eZhu3Christine eNardini4Consiglio Nazionale delle RicerchePartner Institute for Computational BiologyPartner Institute for Computational BiologyPartner Institute for Computational BiologyPartner Institute for Computational BiologyObjective: To provide a frame to estimate the systemic impact (side/adverse events) of (novel) therapeutic targets by taking into consideration drugs potential on the numerous districts involved in rheumatoid arthritis (RA) from the inflammatory and immune response to the gut-intestinal (GI) microbiome.Methods: We curated the collection of molecules from high-throughput screens of diverse (multi-omic) biochemical origin, experimentally associated to RA. Starting from such collection we generated RA-related protein-protein interaction (PPI) networks (interactomes) based on experimental PPI data. Pharmacological treatment simulation, topological and functional analyses were further run to gain insight into the proteins most affected by therapy and by multi-omic modelling.Results: Simulation on the administration of MTX results in the activation of expected (apoptosis) and adverse (nitrogenous metabolism alteration) effects. Growth factor receptor-bound protein 2 (GRB2) and Interleukin-1 Receptor Associated Kinase-4 (IRAK4, already an RA target) emerge as relevant nodes. The former controls the activation of inflammatory, proliferative and degenerative pathways in host and pathogens. The latter controls immune alterations and blocks innate response to pathogens.Conclusions: This multi-omic map properly recollects in a single analytical picture known, yet complex, information like the adverse/side effects of MTX, and provides a reliable platform for in silico hypothesis testing or recommendation on novel therapies. These results can support the development of RA translational research in the design of validation experiments and clinical trials, as such we identify GRB2 as a robust potential new target for RA for its ability to control both synovial degeneracy and dysbiosis, and, conversely, warn on the usage of IRAK4-inhibitors recently promoted, as this involves potential adverse effects in the form of impaired innate response to pathogens.http://journal.frontiersin.org/Journal/10.3389/fcell.2014.00059/fullRheumatoid arthritiscomputational methodsdata integrationprotein-protein interactionnetwork topologymulti-omics
collection DOAJ
language English
format Article
sources DOAJ
author Paolo eTieri
Paolo eTieri
XiaoYuan eZhou
Lisha eZhu
Christine eNardini
spellingShingle Paolo eTieri
Paolo eTieri
XiaoYuan eZhou
Lisha eZhu
Christine eNardini
Multi-omic landscape of Rheumatoid Arthritis: re-evaluation of drug adverse effects
Frontiers in Cell and Developmental Biology
Rheumatoid arthritis
computational methods
data integration
protein-protein interaction
network topology
multi-omics
author_facet Paolo eTieri
Paolo eTieri
XiaoYuan eZhou
Lisha eZhu
Christine eNardini
author_sort Paolo eTieri
title Multi-omic landscape of Rheumatoid Arthritis: re-evaluation of drug adverse effects
title_short Multi-omic landscape of Rheumatoid Arthritis: re-evaluation of drug adverse effects
title_full Multi-omic landscape of Rheumatoid Arthritis: re-evaluation of drug adverse effects
title_fullStr Multi-omic landscape of Rheumatoid Arthritis: re-evaluation of drug adverse effects
title_full_unstemmed Multi-omic landscape of Rheumatoid Arthritis: re-evaluation of drug adverse effects
title_sort multi-omic landscape of rheumatoid arthritis: re-evaluation of drug adverse effects
publisher Frontiers Media S.A.
series Frontiers in Cell and Developmental Biology
issn 2296-634X
publishDate 2014-11-01
description Objective: To provide a frame to estimate the systemic impact (side/adverse events) of (novel) therapeutic targets by taking into consideration drugs potential on the numerous districts involved in rheumatoid arthritis (RA) from the inflammatory and immune response to the gut-intestinal (GI) microbiome.Methods: We curated the collection of molecules from high-throughput screens of diverse (multi-omic) biochemical origin, experimentally associated to RA. Starting from such collection we generated RA-related protein-protein interaction (PPI) networks (interactomes) based on experimental PPI data. Pharmacological treatment simulation, topological and functional analyses were further run to gain insight into the proteins most affected by therapy and by multi-omic modelling.Results: Simulation on the administration of MTX results in the activation of expected (apoptosis) and adverse (nitrogenous metabolism alteration) effects. Growth factor receptor-bound protein 2 (GRB2) and Interleukin-1 Receptor Associated Kinase-4 (IRAK4, already an RA target) emerge as relevant nodes. The former controls the activation of inflammatory, proliferative and degenerative pathways in host and pathogens. The latter controls immune alterations and blocks innate response to pathogens.Conclusions: This multi-omic map properly recollects in a single analytical picture known, yet complex, information like the adverse/side effects of MTX, and provides a reliable platform for in silico hypothesis testing or recommendation on novel therapies. These results can support the development of RA translational research in the design of validation experiments and clinical trials, as such we identify GRB2 as a robust potential new target for RA for its ability to control both synovial degeneracy and dysbiosis, and, conversely, warn on the usage of IRAK4-inhibitors recently promoted, as this involves potential adverse effects in the form of impaired innate response to pathogens.
topic Rheumatoid arthritis
computational methods
data integration
protein-protein interaction
network topology
multi-omics
url http://journal.frontiersin.org/Journal/10.3389/fcell.2014.00059/full
work_keys_str_mv AT paoloetieri multiomiclandscapeofrheumatoidarthritisreevaluationofdrugadverseeffects
AT paoloetieri multiomiclandscapeofrheumatoidarthritisreevaluationofdrugadverseeffects
AT xiaoyuanezhou multiomiclandscapeofrheumatoidarthritisreevaluationofdrugadverseeffects
AT lishaezhu multiomiclandscapeofrheumatoidarthritisreevaluationofdrugadverseeffects
AT christineenardini multiomiclandscapeofrheumatoidarthritisreevaluationofdrugadverseeffects
_version_ 1725744027651801088