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Disease-Associated MRNA Expression Differences in Genes with Low DNA Methylation
Linköping University, Department of Clinical and Experimental Medicine. Linköping University, Faculty of Health Sciences.
Linköping University, Department of Clinical and Experimental Medicine. Linköping University, Faculty of Health Sciences.
Linköping University, Department of Science and Technology. Linköping University, The Institute of Technology.
Mathematical Sciences, Chalmers University of Technology, University of Gothenburg, Gothenburg, Sweden.
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2012 (English)Manuscript (preprint) (Other academic)
Abstract [en]

Although the importance of DNA methylation for mRNA expression has been shown for individualgenes in several complex diseases, such a relation has been difficult to show on a genome-wide scale.Here, we used microarrays to examine the relationship between DNA methylation and mRNAexpression in CD4+ T cells from patients with seasonal allergic rhinitis (SAR) and healthy controls.SAR is an optimal disease model because the disease process can be studied by comparing allergenchallengedCD4+ T cells obtained from patients and controls, and mimicked in Th2 polarised T cellsfrom healthy controls. The cells from patients can be analyzed to study relations between methylationand mRNA expression, while the Th2 cells can be used for functional studies. We found that DNAmethylation, but not mRNA expression clearly separated patients from controls. Similar to studies ofother complex diseases, we found no general relation between DNA methylation and mRNAexpression. However, when we took into account the absence or presence of CpG islands in thepromoters of disease associated genes an association was found: low methylation genes without CpGislands had significantly higher expression levels of disease-associated genes. This association wasconfirmed for genes whose expression levels were regulated by a transcription factor of knownrelevance for allergy, IRF4, using combined ChIP-chip and siRNA mediated silencing of IRF4expression. In summary, disease-associated increases of mRNA expression were found in lowmethylation genes without CpG islands in CD4+ T cells from patients with SAR. Further studies arewarranted to examine if a similar association is found in other complex diseases.

Place, publisher, year, edition, pages
2012.
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:liu:diva-81897OAI: oai:DiVA.org:liu-81897DiVA: diva2:556250
Available from: 2012-09-24 Created: 2012-09-24 Last updated: 2012-09-24Bibliographically approved
In thesis
1. Bioinformatic identification of disease associated pathways by network based analysis
Open this publication in new window or tab >>Bioinformatic identification of disease associated pathways by network based analysis
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Many common diseases are complex, meaning that they are caused by many interacting genes. This makes them difficult to study; to determine disease mechanisms, disease-associated genes must be analyzed in combination. Disease-associated genes can be detected using high-throughput methods, such as mRNA expression microarrays, DNA methylation microarrays and genome-wide association studies (GWAS), but determining how they interact to cause disease is an intricate challenge. One approach is to organize disease-associated genes into networks using protein-protein interactions (PPIs) and dissect them to identify disease causing pathways. Studies of complex disease can also be greatly facilitated by using an appropriate model system. In this dissertation, seasonal allergic rhinitis (SAR) served as a model disease. SAR is a common disease that is relatively easy to study. Also, the key disease cell types, like the CD4+ T cell, are known and can be cultured and activated in vitro by the disease causing pollen.

The aim of this dissertation was to determine network properties of disease-associated genes, and develop methods to identify and validate networks of disease-associated genes. First, we showed that disease-associated genes have distinguishing network properties, one being that they co-localize in the human PPI network. This supported the existence of disease modules within the PPI network. We then identified network modules of genes whose mRNA expression was perturbed in human disease, and showed that the most central genes in those network modules were enriched for disease-associated polymorphisms identified by GWAS. As a case study, we identified disease modules using mRNA expression data from allergen-challenged CD4+ cells from patients with SAR. The case study identified and validated a novel disease-associated gene, FGF2 using GWAS data and RNAi mediated knockdown.

Lastly, we examined how DNA methylation caused disease-associated mRNA expression changes in SAR. DNA methylation, but not mRNA expression profiles, could accurately distinguish allergic patients from healthy controls. Also, we found that disease-associated mRNA expression changes were associated with a low DNA methylation content and absence of CpG islands. Specifically within this group, we found a correlation between disease-associated mRNA expression changes and DNA methylation changes. Using ChIP-chip analysis, we found that targets of a known disease relevant transcription factor, IRF4, were also enriched among non CpG island genes with low methylation levels.

Taken together, in this dissertation the network properties of disease-associated genes were examined, and then used to validate disease networks defined by mRNA expression data. We then examined regulatory mechanisms underlying disease-associated mRNA expression changes in a model disease. These studies support network-based analyses as a method to understand disease mechanisms and identify important disease causing genes, such as treatment targets or markers for personalized medication.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2012. 48 p.
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1326
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-81898 (URN)978-91-7519-802-6 (ISBN)
Public defence
2012-10-12, Linden, Hälsouniversitetet, Campus US, Linköpings universitet, Linköping, 13:00 (English)
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Supervisors
Available from: 2012-09-24 Created: 2012-09-24 Last updated: 2012-09-24Bibliographically approved

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Barrenäs, FredrikBruhn, SörenGustafsson, MikaWang, HuiBenson, Mikael

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