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Benson, Mikael
Publications (10 of 83) Show all publications
Menditto, E., Costa, E., Midão, L., Bosnic-Anticevich, S., Novellino, E., Bialek, S., . . . the, M. g. (2019). Adherence to treatment in allergic rhinitis using mobile technology. The MASK Study. Clinical and Experimental Allergy, 49(4), 442-460
Open this publication in new window or tab >>Adherence to treatment in allergic rhinitis using mobile technology. The MASK Study
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2019 (English)In: Clinical and Experimental Allergy, ISSN 0954-7894, E-ISSN 1365-2222, Vol. 49, no 4, p. 442-460Article in journal (Refereed) Published
Abstract [en]

Background

Mobile technology may help to better understand the adherence to treatment. MASK‐rhinitis (Mobile Airways Sentinel NetworK for allergic rhinitis) is a patient‐centred ICT system. A mobile phone app (the Allergy Diary) central to MASK is available in 22 countries.

Objectives

To assess the adherence to treatment in allergic rhinitis patients using the Allergy DiaryApp.

Methods

An observational cross‐sectional study was carried out on all users who filled in the Allergy Diary from 1 January 2016 to 1 August 2017. Secondary adherence was assessed by using the modified Medication Possession Ratio (MPR) and the Proportion of days covered (PDC) approach.

Results

A total of 12 143 users were registered. A total of 6 949 users reported at least one VAS data recording. Among them, 1 887 users reported ≥7 VAS data. About 1 195 subjects were included in the analysis of adherence. One hundred and thirty‐six (11.28%) users were adherent (MPR ≥70% and PDC ≤1.25), 51 (4.23%) were partly adherent (MPR ≥70% and PDC = 1.50) and 176 (14.60%) were switchers. On the other hand, 832 (69.05%) users were non‐adherent to medications (MPR <70%). Of those, the largest group was non‐adherent to medications and the time interval was increased in 442 (36.68%) users.

Conclusion and clinical relevance

Adherence to treatment is low. The relative efficacy of continuous vs on‐demand treatment for allergic rhinitis symptoms is still a matter of debate. This study shows an approach for measuring retrospective adherence based on a mobile app. This also represents a novel approach for analysing medication‐taking behaviour in a real‐world setting.

Place, publisher, year, edition, pages
Wiley-Blackwell Publishing Inc., 2019
Keywords
adherence; mHealth; mobile technology; observational study; rhinitis; treatment
National Category
Respiratory Medicine and Allergy
Identifiers
urn:nbn:se:liu:diva-158062 (URN)10.1111/cea.13333 (DOI)000463761700007 ()30597673 (PubMedID)2-s2.0-85063011308 (Scopus ID)
Available from: 2019-06-24 Created: 2019-06-24 Last updated: 2019-08-06Bibliographically approved
Benson, M. (2016). Clinical implications of omics and systems medicine: focus on predictive and individualized treatment. Journal of Internal Medicine, 279(3), 229-240
Open this publication in new window or tab >>Clinical implications of omics and systems medicine: focus on predictive and individualized treatment
2016 (English)In: Journal of Internal Medicine, ISSN 0954-6820, E-ISSN 1365-2796, Vol. 279, no 3, p. 229-240Article, review/survey (Refereed) Published
Abstract [en]

Many patients with common diseases do not respond to treatment. This is a key challenge to modern health care, which causes both suffering and enormous costs. One important reason for the lack of treatment response is that common diseases are associated with altered interactions between thousands of genes, in combinations that differ between subgroups of patients who do or do not respond to a given treatment. Such subgroups, or even distinct disease entities, have been described recently in asthma, diabetes, autoimmune diseases and cancer. High-throughput techniques (omics) allow identification and characterization of such subgroups or entities. This may have important clinical implications, such as identification of diagnostic markers for individualized medicine, as well as new therapeutic targets for patients who do not respond to existing drugs. For example, whole-genome sequencing may be applied to more accurately guide treatment of neurodevelopmental diseases, or to identify drugs specifically targeting mutated genes in cancer. A study published in 2015 showed that 28% of hepatocellular carcinomas contained mutated genes that potentially could be targeted by drugs already approved by the US Food and Drug Administration. A translational study, which is described in detail, showed how combined omics, computational, functional and clinical studies could identify and validate a novel diagnostic and therapeutic candidate gene in allergy. Another important clinical implication is the identification of potential diagnostic markers and therapeutic targets for predictive and preventative medicine. By combining computational and experimental methods, early disease regulators may be identified and potentially used to predict and treat disease before it becomes symptomatic. Systems medicine is an emerging discipline, which may contribute to such developments through combining omics with computational, functional and clinical studies. The aims of this review are to provide a brief introduction to systems medicine and discuss how it may contribute to the clinical implementation of individualized treatment, using clinically relevant examples.

Place, publisher, year, edition, pages
WILEY-BLACKWELL, 2016
Keywords
clinical translation; omics; systems medicine
National Category
Clinical Medicine
Identifiers
urn:nbn:se:liu:diva-126821 (URN)10.1111/joim.12412 (DOI)000371617800002 ()26891944 (PubMedID)
Available from: 2016-04-07 Created: 2016-04-05 Last updated: 2017-11-30
Auffray, C., Balling, R., Barroso, I., Bencze, L., Benson, M., Bergeron, J., . . . Zanetti, G. (2016). Making sense of big data in health research: Towards an EU action plan. Genome Medicine, 8(71)
Open this publication in new window or tab >>Making sense of big data in health research: Towards an EU action plan
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2016 (English)In: Genome Medicine, ISSN 1756-994X, E-ISSN 1756-994X, Vol. 8, no 71Article in journal (Refereed) Published
Abstract [en]

Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health arid healthcare for all Europearis.

Place, publisher, year, edition, pages
BIOMED CENTRAL LTD, 2016
National Category
Medical Genetics
Identifiers
urn:nbn:se:liu:diva-130277 (URN)10.1186/s13073-016-0323-y (DOI)000378592900001 ()27338147 (PubMedID)
Note

Funding Agencies|European Union [115568, 603160, 282510, 664691, 115749, 305033, 305397, 288028, 242189, 211601]; European Molecular Biology Laboratory; Wellcome Trust [WT098051]; [115372]; [257082]; [291814]; [291728]; [321567]; [262055]; [115446]; [602552]; [644753]; [634143]; [261357]; [305280]; [115525]; [2011 23 02]; [270089]; [278433]; [602525]; [201418]; [242135]; [260558]; [223411]; [305626]; [115621]; [611388]; [306000]; [354457]; [305564]; [115010]; [269978]

Available from: 2016-08-01 Created: 2016-07-28 Last updated: 2018-01-10
Gustafsson, M., Gawel, D., Alfredsson, L., Baranzini, S., Bjorkander, J., Blomgran, R., . . . Benson, M. (2015). A validated gene regulatory network and GWAS identifies early regulators of T cell-associated diseases. Science Translational Medicine, 7(313), Article ID 313ra178.
Open this publication in new window or tab >>A validated gene regulatory network and GWAS identifies early regulators of T cell-associated diseases
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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
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
National Category
Biological Sciences Clinical Medicine
Identifiers
urn:nbn:se:liu:diva-123522 (URN)10.1126/scitranslmed.aad2722 (DOI)000365237400003 ()26560356 (PubMedID)
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
Bousquet, J., Schunemann, H. J., Fonseca, J., Samolinski, B., Bachert, C., Canonica, G. W., . . . Rodenas, F, . (2015). MACVIA-ARIA Sentinel NetworK for allergic rhinitis (MASK-rhinitis): the new generation guideline implementation. Allergy. European Journal of Allergy and Clinical Immunology, 70(11), 1372-1392
Open this publication in new window or tab >>MACVIA-ARIA Sentinel NetworK for allergic rhinitis (MASK-rhinitis): the new generation guideline implementation
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2015 (English)In: Allergy. European Journal of Allergy and Clinical Immunology, ISSN 0105-4538, E-ISSN 1398-9995, Vol. 70, no 11, p. 1372-1392Article in journal (Refereed) Published
Abstract [en]

Several unmet needs have been identified in allergic rhinitis: identification of the time of onset of the pollen season, optimal control of rhinitis and comorbidities, patient stratification, multidisciplinary team for integrated care pathways, innovation in clinical trials and, above all, patient empowerment. MASK-rhinitis (MACVIA-ARIA Sentinel NetworK for allergic rhinitis) is a simple system centred around the patient which was devised to fill many of these gaps using Information and Communications Technology (ICT) tools and a clinical decision support system (CDSS) based on the most widely used guideline in allergic rhinitis and its asthma comorbidity (ARIA 2015 revision). It is one of the implementation systems of Action Plan B3 of the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA). Three tools are used for the electronic monitoring of allergic diseases: a cell phone-based daily visual analogue scale (VAS) assessment of disease control, CARAT (Control of Allergic Rhinitis and Asthma Test) and e-Allergy screening (premedical system of early diagnosis of allergy and asthma based on online tools). These tools are combined with a clinical decision support system (CDSS) and are available in many languages. An e-CRF and an e-learning tool complete MASK. MASK is flexible and other tools can be added. It appears to be an advanced, global and integrated ICT answer for many unmet needs in allergic diseases which will improve policies and standards.

Place, publisher, year, edition, pages
WILEY-BLACKWELL, 2015
Keywords
allergic rhinitis; ARIA; asthma; Information and communications technology; MACVIA-LR
National Category
Clinical Medicine
Identifiers
urn:nbn:se:liu:diva-122775 (URN)10.1111/all.12686 (DOI)000363329400003 ()26148220 (PubMedID)
Note

Funding Agencies|Chiesi; GSK; Cipla; Sanofi/Regeneron; Novartis; Circassia; Merck; Stallergenes; Medical Research Council; JP Moulton Charitable Foundation; North West Lung Research Centre Charity; European Union; National Institute of Health Research; Thermo Fisher; AstraZeneca; ALK; GlaxoSmithKline; ALK Abello; Merck USA; Biomay; Leti; Biotech Tools; A. Menarini; Aerocrine; Merck Sharp Dohme; Teva; Boehringer Ingelheim; MSD; OrionPharma; Centocor; Sanofi Pasteur; Grunenthal; Synairgen; Stallergens; ALK Abello (Germany/Denmark); Allergopharma (Germany); Stallergenes (Germany/France); HAL Allergy (Germany/the Netherlands); Artu Biologicals (the Netherlands); Allergy Therapeutics/Bencard (UK/Germany); Hartington (Spain); Lofarma (Italy); Novartis/Leti (Germany/Spain); GlaxoSmithKline (UK/Germany); Essex Pharma (Germany); Cytos (Switzerland); Curalogic (Denmark); Roxall (Germany); Biomay (Austria); Thermo Fisher (Germany); Circassia (UK); Biotech Tools s.a. (Belgium); Meda Pharma GmbH (Germany); HAL Allergy (the Netherlands/Germany); Meda (Germany/Sweden); Dutch Lung Foundation; Ubbo Emmius Foundation; Stichting Astma Bestrijding; Adamed; Allergopharma; Almirall; Celon Pharma; FAES; HAL; Meda; Pfizer; Polfarmex; Polpharma; Stallergen; Lekam; UCB; Sanofi; Carnot; Senosiain; Almirral; Jansen; Pearl; Roche; AZ; Astellas; Genentech; Uriach; Abbott Laboratories; ALK-Abello; Ohropax; Servier; Stada; Menarini; Allergy Therapeutics; Bayer; Johnson+ Johnson; Arthrocare; Bencard; BiotechTools; Lofarma; Ursapharm; Bitop; AIPreven; Optima; Torii Co. Ltd.; Shionogi Co. Ltd.; MSD Co. LtD; Tanabe-Mitsubishi; Ono; Taiho; Torii; Kyowa-Kirin; Guidotti-Malesci; Mundipharma; Takeda; Zambon; Chiesi Farmaceutici; Merck Sharp Dohme; DGAKI; GlaxoSmithKline (Germany); Bencard (Germany); Novartis (Germany); Ministry of Science, Education and Sports of Republic of Croatia; Sandoz; Salveo; Schering-Plough; UK National Health Service; British Lung Foundation; AKL Ltd; Eli Lilly; Napp; Orion; Respiratory Effectiveness Group; Zentiva; Efficacy and Mechanism Evaluation programme; HTA; Novartis Farma; Faes Farma; Bial Aristegui; Boehringer; Biomay AG; Vienna, Austria; Uppsala, Sweden

Available from: 2015-12-04 Created: 2015-11-23 Last updated: 2017-12-01
Nestor, C. E., Ottaviano, R., Reinhardt, D., Cruickshanks, H. A., Mjoseng, H. K., McPherson, R. C., . . . Meehan, R. R. (2015). Rapid reprogramming of epigenetic and transcriptional profiles in mammalian culture systems.. Genome Biology, 16, 11
Open this publication in new window or tab >>Rapid reprogramming of epigenetic and transcriptional profiles in mammalian culture systems.
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2015 (English)In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 16, p. 11-Article in journal (Refereed) Published
Abstract [en]

BackgroundThe DNA methylation profile of mammalian cell lines differs from the primary tissue from which they were derived, exhibiting increasing divergence from the in vivo methylation profile with extended time in culture. Few studies have directly examined the initial epigenetic and transcriptional consequences of adaptation of primary mammalian cells to culture, and the potential mechanisms through which this epigenetic dysregulation occurs is unknown.ResultsWe demonstrate that adaptation of mouse embryonic fibroblast, MEFS, to cell culture results in a rapid reprogramming of epigenetic and transcriptional states. We observed global 5-hydroxymethylcytosine (5hmC) erasure within three days of culture initiation. Loss of genic 5hmC was independent of global 5-methylcytosine (5mC) levels and could be partially rescued by addition of Vitamin C. Significantly, 5hmC loss was not linked to concomitant changes in transcription. Discrete promoter-specific gains of 5mC were also observed within seven days of culture initiation. Against this background of global 5hmC loss we identified a handful of developmentally important genes that maintained their 5hmC profile in culture, including the imprinted loci Gnas and H19. Similar outcomes were identified in the adaption of CD4+ T-cells to culture.ConclusionsWe report a dramatic and novel consequence of adaptation of mammalian cells to culture in which global loss of 5hmC occurs; suggesting rapid concomitant loss of methylcytosine dioxygenase activity. The observed epigenetic and transcriptional re-programming occurs much earlier than previously assumed, and has significant implications for the use of cell lines as faithful mimics of in vivo epigenetic and physiological processes.

Place, publisher, year, edition, pages
BioMed Central, 2015
National Category
Other Clinical Medicine
Identifiers
urn:nbn:se:liu:diva-115295 (URN)10.1186/s13059-014-0576-y (DOI)000351819300001 ()25648825 (PubMedID)
Note

We thank Professors Adrian Bird and Nicholas Hastie for their comments on our manuscript. JT and RO are funded by IMI-MARCAR (under grant agreement number (115001) (MARCAR project)). Work in RM's lab is supported by the MRC, IMI-MARCAR and the BBSRC. This work in RM's lab was also initially funded by the Breakthrough Breast Cancer charity. Work in MB's lab was supported by Linkoping University strategic research funding and the Ake Wibergs fund (3772738). Work in SP's lab is supported by the BBSRC.

Available from: 2015-03-12 Created: 2015-03-12 Last updated: 2017-12-04Bibliographically approved
Zhou, Y., Wang, H., Wang, C., Qiu, X., Benson, M., Yin, X., . . . Han, X. (2015). Roles of miRNAs in microcystin-LR-induced Sertoli cell toxicity. Toxicology and Applied Pharmacology, 287(1)
Open this publication in new window or tab >>Roles of miRNAs in microcystin-LR-induced Sertoli cell toxicity
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2015 (English)In: Toxicology and Applied Pharmacology, ISSN 0041-008X, E-ISSN 1096-0333, Vol. 287, no 1Article in journal (Refereed) Published
Abstract [en]

Microcystin (MC)-LR, a cyclic heptapeptide, is a potent reproductive system toxin. To understand the molecular mechanisms of MC-induced reproductive system cytotoxicity, we evaluated global changes of miRNA and mRNA expression in mouse Sertoli cells following MC-LR treatment. Our results revealed that the exposure to MC-LR resulted in an altered miRNA expression profile that might be responsible for the modulation of mRNA expression. Bio-functional analysis indicated that the altered genes were involved in specific cellular processes, including cell death and proliferation. Target gene analysis suggested that junction injury in Sertoli cells exposed to MC-LR might be mediated by miRNAs through the regulation of the Sertoli cell-Sertoli cell pathway. Collectively, these findings may enhance our understanding on the modes of action of MC-LR on mouse Sertoli cells as well as the molecular mechanisms underlying the toxicity of MC-LR on the male reproductive system.

Place, publisher, year, edition, pages
Elsevier, 2015
Keywords
Microcystin-LR; microRNA; mRNA; Sertoli cell; Bioinformatics; Toxicity
National Category
Clinical Medicine
Identifiers
urn:nbn:se:liu:diva-120328 (URN)10.1016/j.taap.2015.05.008 (DOI)000357766400001 ()25986756 (PubMedID)
Note

Funding Agencies|National Natural Science Foundation of China [31370524, 31200401, 21377052, 81170054]; Natural Science Foundation of Jiangsu Province of China [BK2012307, BK20131281, BK2011570]; Specialized Research Fund for Doctoral Program of Higher Education (SRFDP) of Peoples Republic of China [20130091110050]; Open Research Fund of State Key Laboratory of Bioelectronics, Southeast University [G5]

Available from: 2015-07-31 Created: 2015-07-31 Last updated: 2017-12-04
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
Wang, K., Phillips, C. A., Rogers, G. L., Barrenäs, F., Benson, M. & Langston, M. A. (2014). Differential Shannon entropy and differential coefficient of variation: alternatives and augmentations to differential expression in the search for disease-related genes. International journal of computational biology and drug design, 7(2-3), 183-94
Open this publication in new window or tab >>Differential Shannon entropy and differential coefficient of variation: alternatives and augmentations to differential expression in the search for disease-related genes
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2014 (English)In: International journal of computational biology and drug design, ISSN 1756-0756, Vol. 7, no 2-3, p. 183-94Article in journal (Refereed) Published
Abstract [en]

Differential expression has been a standard tool for analysing case-control transcriptomic data since the advent of microarray technology. It has proved invaluable in characterising the molecular mechanisms of disease. Nevertheless, the expression profile of a gene across samples can be perturbed in ways that leave the expression level unaltered, while a biological effect is nonetheless present. This paper describes and analyses differential Shannon entropy and differential coefficient of variation, two alternate techniques for identifying genes of interest. Ontological analysis across 16 human disease datasets demonstrates that these alternatives are effective at identifying disease-related genes not found by mere differential expression alone. Because the two alternate techniques are based on somewhat different mathematical formulations, they tend to produce somewhat different gene lists. Moreover, each may pinpoint genes completely overlooked by the other. Thus, measures of entropy and variation can be used to replace or better yet augment standard differential expression computations.

Place, publisher, year, edition, pages
InderScience Publishers, 2014
National Category
Clinical Medicine
Identifiers
urn:nbn:se:liu:diva-109422 (URN)10.1504/IJCBDD.2014.061656 (DOI)24878729 (PubMedID)
Available from: 2014-08-18 Created: 2014-08-18 Last updated: 2019-02-11Bibliographically approved
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
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