Literature DB >> 29410046

Systems biology and in vitro validation identifies family with sequence similarity 129 member A (FAM129A) as an asthma steroid response modulator.

Michael J McGeachie1, George L Clemmer2, Boris Hayete3, Heming Xing4, Karl Runge3, Ann Chen Wu5, Xiaofeng Jiang6, Quan Lu6, Bruce Church3, Iya Khalil3, Kelan Tantisira7, Scott Weiss7.   

Abstract

BACKGROUND: Variation in response to the most commonly used class of asthma controller medication, inhaled corticosteroids, presents a serious challenge in asthma management, particularly for steroid-resistant patients with little or no response to treatment.
OBJECTIVE: We applied a systems biology approach to primary clinical and genomic data to identify and validate genes that modulate steroid response in asthmatic children.
METHODS: We selected 104 inhaled corticosteroid-treated asthmatic non-Hispanic white children and determined a steroid responsiveness endophenotype (SRE) using observations of 6 clinical measures over 4 years. We modeled each subject's cellular steroid response using data from a previously published study of immortalized lymphoblastoid cell lines under dexamethasone (DEX) and sham treatment. We integrated SRE with immortalized lymphoblastoid cell line DEX responses and genotypes to build a genome-scale network using the Reverse Engineering, Forward Simulation modeling framework, identifying 7 genes modulating SRE.
RESULTS: Three of these genes were functionally validated by using a stable nuclear factor κ-light-chain-enhancer of activated B cells luciferase reporter in A549 human lung epithelial cells, IL-1β cytokine stimulation, and DEX treatment. By using small interfering RNA transfection, knockdown of family with sequence similarity 129 member A (FAM129A) produced a reduction in steroid treatment response (P < .001).
CONCLUSION: With this systems-based approach, we have shown that FAM129A is associated with variation in clinical asthma steroid responsiveness and that FAM129A modulates steroid responsiveness in lung epithelial cells.
Copyright © 2018 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  FAM129A; Inhaled corticosteroids; Reverse Engineering, Forward Simulation modeling; genomics; steroid response endophenotype; systems biology

Mesh:

Substances:

Year:  2018        PMID: 29410046      PMCID: PMC6111005          DOI: 10.1016/j.jaci.2017.11.059

Source DB:  PubMed          Journal:  J Allergy Clin Immunol        ISSN: 0091-6749            Impact factor:   10.793


  43 in total

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Journal:  Bioinformatics       Date:  2007-03-23       Impact factor: 6.937

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Review 8.  Systems biology of asthma and allergic diseases: a multiscale approach.

Authors:  Supinda Bunyavanich; Eric E Schadt
Journal:  J Allergy Clin Immunol       Date:  2014-11-21       Impact factor: 10.793

9.  Causal modeling using network ensemble simulations of genetic and gene expression data predicts genes involved in rheumatoid arthritis.

Authors:  Heming Xing; Paul D McDonagh; Jadwiga Bienkowska; Tanya Cashorali; Karl Runge; Robert E Miller; Dave Decaprio; Bruce Church; Ronenn Roubenoff; Iya G Khalil; John Carulli
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10.  Glucocorticoid repression of inflammatory gene expression shows differential responsiveness by transactivation- and transrepression-dependent mechanisms.

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Journal:  PLoS One       Date:  2013-01-14       Impact factor: 3.240

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  3 in total

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  3 in total

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