A validated gene regulatory network and GWAS identifies early regulators of T cell–associated diseases

Gustafsson, Mika; Gawel, Danuta R.; Alfredsson, Lars; Baranzini, Sergio E.; Björkander, Janne; Blomgran, Robert; Hellberg, Sandra; Eklund, Daniel; Ernerudh, Jan; Kockum, Ingrid; Konstantinell, Aelita; Lahesmaa, Riita; Lentini, Antonio; Liljenström, H. Robert I.; Mattson, Lina; Matussek, Andreas; Mellergård, Johan; Mendez, Melissa; Olsson, Tomas; Pujana, Miguel Ángel; Rasool, Omid; Serra-Musach, Jordi; Stenmarker, Margaretha; Tripathi, Subhash; Viitala, Miro; Wang, Hui; Zhang, Huan; Nestor, Colm E.; Benson, Mikael

doi:10.1126/scitranslmed.aad2722

Cited by 69 publications

(84 citation statements)

References 47 publications

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“…The expression of genes reacting when challenged with allergen differed greatly, but not completely, between patients before treatment and healthy controls. This is in agreement with previous studies by us and others showing that CD4 + T cells from healthy controls also respond to allergen challenge [15, 16]. …”

Section: Resultssupporting

confidence: 94%

Potential Involvement of Type I Interferon Signaling in Immunotherapy in Seasonal Allergic Rhinitis

Mattson

Lentini

Gawel

et al. 2016

Journal of Immunology Research

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Specific immunotherapy (SIT) reverses the symptoms of seasonal allergic rhinitis (SAR) in most patients. Recent studies report type I interferons shifting the balance between type I T helper cell (Th1) and type II T helper cells (Th2) towards Th2 dominance by inhibiting the differentiation of naive T cells into Th1 cells. As SIT is thought to cause a shift towards Th1 dominance, we hypothesized that SIT would alter interferon type I signaling. To test this, allergen and diluent challenged CD4+ T cells from healthy controls and patients from different time points were analyzed. The initial experiments focused on signature genes of the pathway and found complex changes following immunotherapy, which were consistent with our hypothesis. As interferon signaling involves multiple genes, expression profiling studies were performed, showing altered expression of the pathway. These findings require validation in a larger group of patients in further studies.

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Section: Resultssupporting

confidence: 94%

Potential Involvement of Type I Interferon Signaling in Immunotherapy in Seasonal Allergic Rhinitis

Mattson

Lentini

Gawel

et al. 2016

Journal of Immunology Research

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“…However, we agree with Gomez and Kaminski[56] in thinking that large prospective clinical studies will be needed to test the usefulness of these immune signatures in predicting suboptimal asthma control over time. It may be possible to refine such approaches by identifying specific cells and regulatory events underlying such immune signatures, both in asthma and other settings[57–60]. The need for large prospective studies to evaluate the clinical utility of immune monitoring assays is similar to proposals for validating pharmacogenomic assays and predictions, including in the area of asthma therapy[61,62].…”

Section: Therapy Selection and Monitoringmentioning

confidence: 99%

Immune monitoring for precision medicine in allergy and asthma

Boyd

Hoh

Galli

2017

Current Opinion in Immunology

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“Precision Medicine” embodies the analyses of extensive data collected from patients and their environments to identify and apply patient-specific prophylactic strategies and medical treatments to improve clinical outcomes and healthcare cost-effectiveness. Many new methods have been developed for evaluating the activity of the human immune system. Such “immune monitoring” approaches are now being used in studies of allergy and asthma in the hope of identifying better correlates of disease status, predictors of therapeutic outcomes, and potential side-effects of treatment. Together with analyses of family histories, genetic and other biometric data, and measurements of exposures to environmental and other risk factors for developing or exacerbating disease, immune monitoring approaches promise to enable “Precision Medicine” for allergic diseases and asthma.

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“…learning networks, produce large regulatory network models that tremendously vary in accuracy, comprehension, and model complexity (depending on the biological system and the technologies and methods used for network modeling and learning) [2][3][4] . This perspective piece will not provide a comprehensive review of all these methods (or all the large-scale genomics efforts that produce the required data sets); instead, we aim to provide an overview of a few core features that the network inference methods of the future will need to incorporate.…”

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confidence: 99%

Biophysically Motivated Regulatory Network Inference: Progress and Prospects

Äijö

Bonneau²

2016

Hum Hered

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Thanks to the confluence of genomic technology and computational developments, the possibility of network inference methods that automatically learn large comprehensive models of cellular regulation is closer than ever. This perspective focuses on enumerating the elements of computational strategies that, when coupled to appropriate experimental designs, can lead to accurate large-scale models of chromatin state and transcriptional regulatory structure and dynamics. We highlight 4 research questions that require further investigation in order to make progress in network inference: (1) using overall constraints on network structure such as sparsity, (2) use of informative priors and data integration to constrain individual model parameters, (3) estimation of latent regulatory factor activity under varying cell conditions, and (4) new methods for learning and modeling regulatory factor interactions. We conclude that methods combining advances in these 4 categories of required effort with new genomic technologies will result in biophysically motivated dynamic genome-wide regulatory network models for several of the best-studied organisms and cell types.

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A validated gene regulatory network and GWAS identifies early regulators of T cell–associated diseases

Cited by 69 publications

References 47 publications

Potential Involvement of Type I Interferon Signaling in Immunotherapy in Seasonal Allergic Rhinitis

Potential Involvement of Type I Interferon Signaling in Immunotherapy in Seasonal Allergic Rhinitis

Immune monitoring for precision medicine in allergy and asthma

Biophysically Motivated Regulatory Network Inference: Progress and Prospects

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