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A validated gene regulatory network and GWAS identifies early regulators of T cell-associated diseases
Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Medicine and Health Sciences.
Karolinska Institute, Sweden.
University of Calif San Francisco, CA, USA.
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2015 (English)In: Science Translational Medicine, ISSN 1946-6234, E-ISSN 1946-6242, Vol. 7, no 313, article id 313ra178Article in journal (Refereed) Published
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Text
Abstract [en]

Early regulators of disease may increase understanding of disease mechanisms and serve as markers for presymptomatic diagnosis and treatment. However, early regulators are difficult to identify because patients generally present after they are symptomatic. We hypothesized that early regulators of T cell-associated diseases could be found by identifying upstream transcription factors (TFs) in T cell differentiation and by prioritizing hub TFs that were enriched for disease-associated polymorphisms. A gene regulatory network (GRN) was constructed by time series profiling of the transcriptomes and methylomes of human CD4(+) T cells during in vitro differentiation into four helper T cell lineages, in combination with sequence-based TF binding predictions. The TFs GATA3, MAF, and MYB were identified as early regulators and validated by ChIP-seq (chromatin immunoprecipitation sequencing) and small interfering RNA knockdowns. Differential mRNA expression of the TFs and their targets in T cell-associated diseases supports their clinical relevance. To directly test if the TFs were altered early in disease, T cells from patients with two T cell-mediated diseases, multiple sclerosis and seasonal allergic rhinitis, were analyzed. Strikingly, the TFs were differentially expressed during asymptomatic stages of both diseases, whereas their targets showed altered expression during symptomatic stages. This analytical strategy to identify early regulators of disease by combining GRNs with genome-wide association studies may be generally applicable for functional and clinical studies of early disease development.

Place, publisher, year, edition, pages
AMER ASSOC ADVANCEMENT SCIENCE , 2015. Vol. 7, no 313, article id 313ra178
National Category
Biological Sciences Clinical Medicine
Identifiers
URN: urn:nbn:se:liu:diva-123522DOI: 10.1126/scitranslmed.aad2722ISI: 000365237400003PubMedID: 26560356OAI: oai:DiVA.org:liu-123522DiVA, id: diva2:886275
Note

Funding Agencies|Cancer fund, Swedish Medical Research Council [K2013-61X-22310-01-04, 2012-3168]; Academy of Finland Centre of Excellence in Molecular Systems Immunology and Physiology Research [250114]; Sigrid Juselius Foundation; Generalitat de Catalunya AGAUR [2014-SGR364]; Spanish Association Against Cancer; Spanish Ministry of Health ISCIII FIS [PI12/01528]; RTICC [RD12/0036/0008]

Available from: 2015-12-22 Created: 2015-12-21 Last updated: 2018-04-10Bibliographically approved
In thesis
1. Identification of genes and regulators that are shared across T cell associated diseases
Open this publication in new window or tab >>Identification of genes and regulators that are shared across T cell associated diseases
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Genome-wide association studies (GWASs) of hundreds of diseases and millions of patients have led to the identification of genes that are associated with more than one disease. The aims of this PhD thesis were to a) identify a group of genes important in multiple diseases (shared disease genes), b) identify shared up-stream disease regulators, and c) determine how the same genes can be involved in the pathogenesis of different diseases. These aims have been tested on CD4+ T cells because they express the T helper cell differentiation pathway, which was the most enriched pathway in analyses of all disease associated genes identified with GWASs.

Combining information about known gene-gene interactions from the protein-protein interaction (PPI) network with gene expression changes in multiple T cell associated diseases led to the identification of a group of highly interconnected genes that were miss-expressed in many of those diseases – hereafter called ‘shared disease genes’. Those genes were further enriched for inflammatory, metabolic and proliferative pathways, genetic variants identified by all GWASs, as well as mutations in cancer studies and known diagnostic and therapeutic targets. Taken together, these findings supported the relevance of the shared disease genes.

Identification of the shared upstream disease regulators was addressed in the second project of this PhD thesis. The underlying hypothesis assumed that the determination of the shared upstream disease regulators is possible through a network model showing in which order genes activate each other. For that reason a transcription factor–gene regulatory network (TF-GRN) was created. The TF-GRN was based on the time-series gene expression profiling of the T helper cell type 1 (Th1), and T helper cell type 2 (Th2) differentiation from Native T-cells. Transcription factors (TFs) whose expression changed early during polarization and had many downstream predicted targets (hubs) that were enriched for disease associated single nucleotide polymorphisms (SNPs) were prioritised as the putative early disease regulators. These analyses identified three transcription factors: GATA3, MAF and MYB. Their predicted targets were validated by ChIP-Seq and siRNA mediated knockdown in primary human T-cells. CD4+ T cells isolated from seasonal allergic rhinitis (SAR) and multiple sclerosis (MS) patients in their non-symptomatic stages were analysed in order to demonstrate predictive potential of those three TFs. We found that those three TFs were differentially expressed in symptom-free stages of the two diseases, while their TF-GRN{predicted targets were differentially expressed during symptomatic disease stages. Moreover, using RNA-Seq data we identified a disease associated SNP that correlated with differential splicing of GATA3.

A limitation of the above study is that it concentrated on TFs as main regulators in cells, excluding other potential regulators such as microRNAs. To this end, a microRNA{gene regulatory network (mGRN) of human CD4+ T cell differentiation was constructed. Within this network, we defined regulatory clusters (groups of microRNAs that are regulating groups of mRNAs). One regulatory cluster was differentially expressed in all of the tested diseases, and was highly enriched for GWAS SNPs. Although the microRNA processing machinery was dynamically upregulated during early T-cell activation, the majority of microRNA modules showed specialisation in later time-points.

In summary this PhD thesis shows the relevance of shared genes and up-stream disease regulators. Putative mechanisms of why shared genes can be involved in pathogenesis of different diseases have also been demonstrated: a) differential gene expression in different diseases; b) alternative transcription factor splicing variants may affect different downstream gene target group; and c) SNPs might cause alternative splicing.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2018. p. 95
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1618
National Category
Medical Genetics
Identifiers
urn:nbn:se:liu:diva-147047 (URN)10.3384/diss.diva-147047 (DOI)9789176853207 (ISBN)
Public defence
2018-05-09, Eken, Campus US, Linköping, 09:00 (English)
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Supervisors
Available from: 2018-04-10 Created: 2018-04-10 Last updated: 2018-04-10Bibliographically approved

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Gustafsson, MikaGawel, DanutaBlomgran, RobertHellberg, SandraEklund, DanielErnerudh, JanLentini, AntonioMellergård, JohanWang, HuiZhang, HuanNestor, ColmBenson, Mikael

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Gustafsson, MikaGawel, DanutaBlomgran, RobertHellberg, SandraEklund, DanielErnerudh, JanLentini, AntonioMellergård, JohanWang, HuiZhang, HuanNestor, ColmBenson, Mikael
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