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Barrenäs, Fredrik
Publications (10 of 14) Show all publications
Bruhn, S., Fang, Y., Barrenäs, F., Gustafsson, M., Zhang, H., Konstantinell, A., . . . Benson, M. (2014). A Generally Applicable Translational Strategy Identifies S100A4 as a Candidate Gene in Allergy. Science Translational Medicine, 6(218)
Open this publication in new window or tab >>A Generally Applicable Translational Strategy Identifies S100A4 as a Candidate Gene in Allergy
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2014 (English)In: Science Translational Medicine, ISSN 1946-6234, E-ISSN 1946-6242, Vol. 6, no 218Article in journal (Refereed) Published
Abstract [en]

The identification of diagnostic markers and therapeutic candidate genes in common diseases is complicated by the involvement of thousands of genes. We hypothesized that genes co-regulated with a key gene in allergy, IL13, would form a module that could help to identify candidate genes. We identified a T helper 2 (T(H)2) cell module by small interfering RNA-mediated knockdown of 25 putative IL13-regulating transcription factors followed by expression profiling. The module contained candidate genes whose diagnostic potential was supported by clinical studies. Functional studies of human TH2 cells as well as mouse models of allergy showed that deletion of one of the genes, S100A4, resulted in decreased signs of allergy including TH2 cell activation, humoral immunity, and infiltration of effector cells. Specifically, dendritic cells required S100A4 for activating T cells. Treatment with an anti-S100A4 antibody resulted in decreased signs of allergy in the mouse model as well as in allergen-challenged T cells from allergic patients. This strategy, which may be generally applicable to complex diseases, identified and validated an important diagnostic and therapeutic candidate gene in allergy.

Place, publisher, year, edition, pages
American Association for the Advancement of Science, 2014
National Category
Clinical Medicine Basic Medicine
Identifiers
urn:nbn:se:liu:diva-104118 (URN)10.1126/scitranslmed.3007410 (DOI)000329789600003 ()
Available from: 2014-02-07 Created: 2014-02-07 Last updated: 2018-01-11
Nestor, C., Barrenäs, F., Wang, H., Lentini, A., Zhang, H., Bruhn, S., . . . Benson, M. (2014). DNA Methylation Changes Separate Allergic Patients from Healthy Controls and May Reflect Altered CD4(+) T-Cell Population Structure. PLoS Genetics, 10(1), e1004059
Open this publication in new window or tab >>DNA Methylation Changes Separate Allergic Patients from Healthy Controls and May Reflect Altered CD4(+) T-Cell Population Structure
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2014 (English)In: PLoS Genetics, ISSN 1553-7390, E-ISSN 1553-7404, Vol. 10, no 1, p. e1004059-Article in journal (Refereed) Published
Abstract [en]

Altered DNA methylation patterns in CD4(+) T-cells indicate the importance of epigenetic mechanisms in inflammatory diseases. However, the identification of these alterations is complicated by the heterogeneity of most inflammatory diseases. Seasonal allergic rhinitis (SAR) is an optimal disease model for the study of DNA methylation because of its welldefined phenotype and etiology. We generated genome-wide DNA methylation (N-patients = 8, N-controls = 8) and gene expression (N-patients = 9, N-controls = 10) profiles of CD4(+) T-cells from SAR patients and healthy controls using Illuminas HumanMethylation450 and HT-12 microarrays, respectively. DNA methylation profiles clearly and robustly distinguished SAR patients from controls, during and outside the pollen season. In agreement with previously published studies, gene expression profiles of the same samples failed to separate patients and controls. Separation by methylation (N-patients = 12, N-controls = 12), but not by gene expression (N-patients = 21, N-controls = 21) was also observed in an in vitro model system in which purified PBMCs from patients and healthy controls were challenged with allergen. We observed changes in the proportions of memory T-cell populations between patients (N-patients = 35) and controls (N-controls = 12), which could explain the observed difference in DNA methylation. Our data highlight the potential of epigenomics in the stratification of immune disease and represents the first successful molecular classification of SAR using CD4(+) T cells.

Place, publisher, year, edition, pages
Public Library of Science, 2014
National Category
Clinical Medicine Basic Medicine
Identifiers
urn:nbn:se:liu:diva-107871 (URN)10.1371/journal.pgen.1004059 (DOI)000336525000030 ()
Available from: 2014-06-23 Created: 2014-06-23 Last updated: 2019-02-11
Schoenrock, A., Samanfar, B., Pitre, S., Hooshyar, M., Jin, K., Phillips, C. A., . . . Golshani, A. (2014). Efficient prediction of human protein-protein interactions at a global scale. BMC bioinformatics, 15(1), 383
Open this publication in new window or tab >>Efficient prediction of human protein-protein interactions at a global scale
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2014 (English)In: BMC bioinformatics, ISSN 1471-2105, Vol. 15, no 1, p. 383-Article in journal (Refereed) Published
Abstract [en]

BackgroundOur knowledge of global protein-protein interaction (PPI) networks in complex organisms such as humans is hindered by technical limitations of current methods.ResultsOn the basis of short co-occurring polypeptide regions, we developed a tool called MP-PIPE capable of predicting a global human PPI network within 3 months. With a recall of 23% at a precision of 82.1%, we predicted 172,132 putative PPIs. We demonstrate the usefulness of these predictions through a range of experiments.ConclusionsThe speed and accuracy associated with MP-PIPE can make this a potential tool to study individual human PPI networks (from genomic sequences alone) for personalized medicine.

Place, publisher, year, edition, pages
BioMed Central, 2014
National Category
Clinical Medicine
Identifiers
urn:nbn:se:liu:diva-114135 (URN)10.1186/s12859-014-0383-1 (DOI)000347647900001 ()25492630 (PubMedID)
Available from: 2015-02-10 Created: 2015-02-10 Last updated: 2015-04-10Bibliographically approved
Gustafsson, M., Edström, M., Gawel, D., Nestor, C., Wang, H., Zhang, H., . . . Benson, M. (2014). Integrated genomic and prospective clinical studies show the importance of modular pleiotropy for disease susceptibility, diagnosis and treatment. Genome Medicine, 6(17)
Open this publication in new window or tab >>Integrated genomic and prospective clinical studies show the importance of modular pleiotropy for disease susceptibility, diagnosis and treatment
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2014 (English)In: Genome Medicine, ISSN 1756-994X, E-ISSN 1756-994X, Vol. 6, no 17Article in journal (Refereed) Published
Abstract [en]

Background: Translational research typically aims to identify and functionally validate individual, disease-specific genes. However, reaching this aim is complicated by the involvement of thousands of genes in common diseases, and that many of those genes are pleiotropic, that is, shared by several diseases. Methods: We integrated genomic meta-analyses with prospective clinical studies to systematically investigate the pathogenic, diagnostic and therapeutic roles of pleiotropic genes. In a novel approach, we first used pathway analysis of all published genome-wide association studies (GWAS) to find a cell type common to many diseases. Results: The analysis showed over-representation of the T helper cell differentiation pathway, which is expressed in T cells. This led us to focus on expression profiling of CD4(+) T cells from highly diverse inflammatory and malignant diseases. We found that pleiotropic genes were highly interconnected and formed a pleiotropic module, which was enriched for inflammatory, metabolic and proliferative pathways. The general relevance of this module was supported by highly significant enrichment of genetic variants identified by all GWAS and cancer studies, as well as known diagnostic and therapeutic targets. Prospective clinical studies of multiple sclerosis and allergy showed the importance of both pleiotropic and disease specific modules for clinical stratification. Conclusions: In summary, this translational genomics study identified a pleiotropic module, which has key pathogenic, diagnostic and therapeutic roles.

Place, publisher, year, edition, pages
BioMed Central, 2014
National Category
Clinical Medicine Basic Medicine
Identifiers
urn:nbn:se:liu:diva-106873 (URN)10.1186/gm534 (DOI)000334631300002 ()
Available from: 2014-05-28 Created: 2014-05-23 Last updated: 2020-01-16
Chavali, S., Bruhn, S., Tiemann, K., Sætrom, P., Barrenäs, F., Saito, T., . . . Benson, M. (2013). MicroRNAs act complementarily to regulate disease-related mRNA modules in human diseases. RNA: A publication of the RNA Society, 19(11), 1552-1562
Open this publication in new window or tab >>MicroRNAs act complementarily to regulate disease-related mRNA modules in human diseases
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2013 (English)In: RNA: A publication of the RNA Society, ISSN 1355-8382, E-ISSN 1469-9001, Vol. 19, no 11, p. 1552-1562Article in journal (Refereed) Published
Abstract [en]

MicroRNAs (miRNAs) play a key role in regulating mRNA expression, and individual miRNAs have been proposed as diagnostic and therapeutic candidates. The identification of such candidates is complicated by the involvement of multiple miRNAs and mRNAs as well as unknown disease topology of the miRNAs. Here, we investigated if disease-associated miRNAs regulate modules of disease-associated mRNAs, if those miRNAs act complementarily or synergistically, and if single or combinations of miRNAs can be targeted to alter module functions. We first analyzed publicly available miRNA and mRNA expression data for five different diseases. Integrated target prediction and network-based analysis showed that the miRNAs regulated modules of disease-relevant genes. Most of the miRNAs acted complementarily to regulate multiple mRNAs. To functionally test these findings, we repeated the analysis using our own miRNA and mRNA expression data from CD4+ T cells from patients with seasonal allergic rhinitis. This is a good model of complex diseases because of its well-defined phenotype and pathogenesis. Combined computational and functional studies confirmed that miRNAs mainly acted complementarily and that a combination of two complementary miRNAs, miR-223 and miR-139-3p, could be targeted to alter disease-relevant module functions, namely, the release of type 2 helper T-cell (Th2) cytokines. Taken together, our findings indicate that miRNAs act complementarily to regulate modules of disease-related mRNAs and can be targeted to alter disease-relevant functions.

Place, publisher, year, edition, pages
Cold Spring Harbor Laboratory Press (CSHL), 2013
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-99867 (URN)10.1261/rna.038414.113 (DOI)000325813900010 ()24062574 (PubMedID)
Available from: 2013-10-22 Created: 2013-10-22 Last updated: 2017-12-06Bibliographically approved
Barrenäs, F. (2012). Bioinformatic identification of disease associated pathways by network based analysis. (Doctoral dissertation). Linköping: Linköping University Electronic Press
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. p. 48
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)
Opponent
Supervisors
Available from: 2012-09-24 Created: 2012-09-24 Last updated: 2019-12-10Bibliographically approved
Barrenäs, F., Bruhn, S., Gustafsson, M., Jörnsten, R., Langston, M. A., Nestor, C., . . . Benson, M. (2012). Disease-Associated MRNA Expression Differences in Genes with Low DNA Methylation.
Open this publication in new window or tab >>Disease-Associated MRNA Expression Differences in Genes with Low DNA Methylation
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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.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-81897 (URN)
Available from: 2012-09-24 Created: 2012-09-24 Last updated: 2012-09-24Bibliographically approved
Barrenäs, F., Chavali, S., Alves, A. C., Coin, L., Jarvelin, M.-R., Jörnsten, R., . . . Benson, M. (2012). Highly interconnected genes in disease-specific networks are enriched for disease-associated polymorphisms. Genome Biology, 13(6), R46
Open this publication in new window or tab >>Highly interconnected genes in disease-specific networks are enriched for disease-associated polymorphisms
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2012 (English)In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 13, no 6, p. R46-Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Complex diseases are associated with altered interactions between thousands of genes. We developed a novel method to identify and prioritize disease genes, which was generally applicable to complex diseases.

RESULTS: We identified modules of highly interconnected genes in disease-specific networks derived from integrating gene-expression and protein interaction data. We examined if those modules were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies. First, we analyzed publicly available gene expression microarray and genome-wide association study (GWAS) data from 13, highly diverse, complex diseases. In each disease, highly interconnected genes formed modules, which were significantly enriched for genes harboring disease-associated SNPs. To test if such modules could be used to find novel genes for functional studies, we repeated the analyses using our own gene expression microarray and GWAS data from seasonal allergic rhinitis. We identified a novel gene, FGF2, whose relevance was supported by functional studies using combined small interfering RNA-mediated knock-down and gene expression microarrays. The modules in the 13 complex diseases analyzed here tended to overlap and were enriched for pathways related to oncological, metabolic and inflammatory diseases. This suggested that this union of the modules would be associated with a general increase in susceptibility for complex diseases. Indeed, we found that this union was enriched with GWAS genes for 145 other complex diseases.

CONCLUSIONS: Modules of highly interconnected complex disease genes were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies.

Place, publisher, year, edition, pages
BioMed Central, 2012
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-81896 (URN)10.1186/gb-2012-13-6-r46 (DOI)000308546300006 ()22703998 (PubMedID)
Note

funding agencies|European Community|223367|US National Institutes of Health|R01-AA-0187763P20MD000516-07S1|Swedish Research Council||

Available from: 2012-09-24 Created: 2012-09-24 Last updated: 2017-12-07Bibliographically approved
Bruhn, S., Barrenäs, F., Mobini, R., Andersson, B. A., Chavali, S., Egan, B. S., . . . Benson, M. (2012). Increased expression of IRF4 and ETS1 in CD4+ cells from patients with intermittent allergic rhinitis. Allergy. European Journal of Allergy and Clinical Immunology, 67(1), 33-40
Open this publication in new window or tab >>Increased expression of IRF4 and ETS1 in CD4+ cells from patients with intermittent allergic rhinitis
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2012 (English)In: Allergy. European Journal of Allergy and Clinical Immunology, ISSN 0105-4538, E-ISSN 1398-9995, Vol. 67, no 1, p. 33-40Article in journal (Refereed) Published
Abstract [en]

Background: The transcription factor (TF) IRF4 is involved in the regulation of Th1, Th2, Th9, and Th17 cells, and animal studies have indicated an important role in allergy. However, IRF4 and its target genes have not been examined in human allergy. Methods: IRF4 and its target genes were examined in allergen-challenged CD4+ cells from patients with IAR, using combined gene expression microarrays and chromatin immunoprecipitation chips (ChIP-chips), computational target prediction, and RNAi knockdowns. Results: IRF4 increased in allergen-challenged CD4+ cells from patients with IAR, and functional studies supported its role in Th2 cell activation. IRF4 ChIP-chip showed that IRF4 regulated a large number of genes relevant to Th cell differentiation. However, neither Th1 nor Th2 cytokines were the direct targets of IRF4. To examine whether IRF4 induced Th2 cytokines via one or more downstream TFs, we combined gene expression microarrays, ChIP-chips, and computational target prediction and found a putative intermediary TF, namely ETS1 in allergen-challenged CD4+ cells from allergic patients. ETS1 increased significantly in allergen-challenged CD4+ cells from patients compared to controls. Gene expression microarrays before and after ETS1 RNAi knockdown showed that ETS1 induced Th2 cytokines as well as disease-related pathways. Conclusions: Increased expression of IRF4 in allergen-challenged CD4+ cells from patients with intermittent allergic rhinitis leads to activation of a complex transcriptional program, including Th2 cytokines.

Place, publisher, year, edition, pages
John Wiley and Sons, 2012
Keywords
Allergy, transcription factor
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-75112 (URN)10.1111/j.1398-9995.2011.02707.x (DOI)000297921100007 ()
Note
Funding Agencies|European Commission|223367|MultiMod||Swedish Medical Research Council||US National Institutes of Health|P01-DA-015027-01R01-MH-074460-01U01-AA-013512U01-AA-013641-04|US Department of Energy under the EPSCoR Laboratory||Available from: 2012-02-21 Created: 2012-02-17 Last updated: 2017-12-07
Sjogren, A.-K. M., Barrenäs, F., Muraro, A., Gustafsson, M., Saetrom, P., Wang, H. & Benson, M. (2012). Monozygotic twins discordant for intermittent allergic rhinitis differ in mRNA and protein levels. Allergy. European Journal of Allergy and Clinical Immunology, 67(6), 831-833
Open this publication in new window or tab >>Monozygotic twins discordant for intermittent allergic rhinitis differ in mRNA and protein levels
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2012 (English)In: Allergy. European Journal of Allergy and Clinical Immunology, ISSN 0105-4538, E-ISSN 1398-9995, Vol. 67, no 6, p. 831-833Article in journal (Refereed) Published
Abstract [en]

Monozygotic (MZ) twins discordant for complex diseases may help to find disease mechanisms that are not due to genetic variants. Intermittent allergic rhinitis (IAR) is an optimal disease model because it occurs at defined time points each year, owing to known external antigens. We hypothesized that MZ twins discordant for IAR could help to find gene expression differences that are not dependent on genetic variants. We collected blood outside of the season from MZ twins discordant for IAR, challenged their peripheral blood mononuclear cells (PBMC) with pollen allergen in vitro, collected supernatants and isolated CD4+ T cells. We identified disease-relevant mRNAs and proteins that differed between the discordant MZ twins. By contrast, no differences in microRNA expression were found. Our results indicate that MZ twins discordant for IAR is an optimal model to identify disease mechanisms that are not due to genetic variants.

Place, publisher, year, edition, pages
John Wiley and Sons, 2012
Keywords
allergens, CD4+T cells, clinical immunology, discordant twins
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-78268 (URN)10.1111/j.1398-9995.2012.02828.x (DOI)000303854900017 ()
Note

Funding Agencies|European Commission|223367|Swedish Research Council||

Available from: 2012-06-08 Created: 2012-06-08 Last updated: 2017-12-07Bibliographically approved
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