Literature DB >> 26560356

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

Mika Gustafsson1, Danuta R Gawel2, Lars Alfredsson3, Sergio Baranzini4, Janne Björkander5, Robert Blomgran6, Sandra Hellberg7, Daniel Eklund8, Jan Ernerudh9, Ingrid Kockum10, Aelita Konstantinell11, Riita Lahesmaa12, Antonio Lentini2, H Robert I Liljenström2, Lina Mattson2, Andreas Matussek5, Johan Mellergård13, Melissa Mendez14, Tomas Olsson10, Miguel A Pujana15, Omid Rasool12, Jordi Serra-Musach15, Margaretha Stenmarker5, Subhash Tripathi12, Miro Viitala12, Hui Wang16, Huan Zhang2, Colm E Nestor2, Mikael Benson17.   

Abstract

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.
Copyright © 2015, American Association for the Advancement of Science.

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Year:  2015        PMID: 26560356     DOI: 10.1126/scitranslmed.aad2722

Source DB:  PubMed          Journal:  Sci Transl Med        ISSN: 1946-6234            Impact factor:   17.956


  32 in total

1.  Time-resolved transcriptome and proteome landscape of human regulatory T cell (Treg) differentiation reveals novel regulators of FOXP3.

Authors:  Angelika Schmidt; Francesco Marabita; Narsis A Kiani; Catharina C Gross; Henrik J Johansson; Szabolcs Éliás; Sini Rautio; Matilda Eriksson; Sunjay Jude Fernandes; Gilad Silberberg; Ubaid Ullah; Urvashi Bhatia; Harri Lähdesmäki; Janne Lehtiö; David Gomez-Cabrero; Heinz Wiendl; Riitta Lahesmaa; Jesper Tegnér
Journal:  BMC Biol       Date:  2018-05-07       Impact factor: 7.431

Review 2.  Genome editing to define the function of risk loci and variants in rheumatic disease.

Authors:  Yuriy Baglaenko; Dana Macfarlane; Alexander Marson; Peter A Nigrovic; Soumya Raychaudhuri
Journal:  Nat Rev Rheumatol       Date:  2021-06-29       Impact factor: 20.543

Review 3.  Using GWAS to identify novel therapeutic targets for osteoporosis.

Authors:  Olivia L Sabik; Charles R Farber
Journal:  Transl Res       Date:  2016-10-27       Impact factor: 7.012

4.  Integrating GWAS and Co-expression Network Data Identifies Bone Mineral Density Genes SPTBN1 and MARK3 and an Osteoblast Functional Module.

Authors:  Gina M Calabrese; Larry D Mesner; Joseph P Stains; Steven M Tommasini; Mark C Horowitz; Clifford J Rosen; Charles R Farber
Journal:  Cell Syst       Date:  2016-11-17       Impact factor: 10.304

Review 5.  The Genetics of Multiple Sclerosis: From 0 to 200 in 50 Years.

Authors:  Sergio E Baranzini; Jorge R Oksenberg
Journal:  Trends Genet       Date:  2017-10-05       Impact factor: 11.639

6.  Characterization of Transcriptional Regulatory Networks that Promote and Restrict Identities and Functions of Intestinal Innate Lymphoid Cells.

Authors:  Maria Pokrovskii; Jason A Hall; David E Ochayon; Ren Yi; Natalia S Chaimowitz; Harsha Seelamneni; Nicholas Carriero; Aaron Watters; Stephen N Waggoner; Dan R Littman; Richard Bonneau; Emily R Miraldi
Journal:  Immunity       Date:  2019-07-02       Impact factor: 31.745

7.  EyeDiseases: an integrated resource for dedicating to genetic variants, gene expression and epigenetic factors of human eye diseases.

Authors:  Jian Yuan; Fukun Chen; Dandan Fan; Qi Jiang; Zhengbo Xue; Ji Zhang; Xiangyi Yu; Kai Li; Jia Qu; Jianzhong Su
Journal:  NAR Genom Bioinform       Date:  2021-06-01

Review 8.  Immune monitoring for precision medicine in allergy and asthma.

Authors:  Scott Dexter Boyd; Ramona Amy Hoh; Kari Christine Nadeau; Stephen Joseph Galli
Journal:  Curr Opin Immunol       Date:  2017-09-07       Impact factor: 7.486

9.  Perspectives in immunotherapy: meeting report from the immunotherapy bridge (December 2nd-3rd, 2020, Italy).

Authors:  Paolo A Ascierto; Carlo Bifulco; Fortunato Ciardiello; Sandra Demaria; Leisha A Emens; Robert Ferris; Silvia C Formenti; Jerome Galon; Samir N Khleif; Tomas Kirchhoff; Jennifer McQuade; Kunle Odunsi; Akash Patnaik; Chrystal M Paulos; Janis M Taube; John Timmerman; Bernard A Fox; Patrick Hwu; Igor Puzanov
Journal:  J Transl Med       Date:  2021-06-02       Impact factor: 5.531

10.  5-Hydroxymethylcytosine Remodeling Precedes Lineage Specification during Differentiation of Human CD4(+) T Cells.

Authors:  Colm E Nestor; Antonio Lentini; Cathrine Hägg Nilsson; Danuta R Gawel; Mika Gustafsson; Lina Mattson; Hui Wang; Olof Rundquist; Richard R Meehan; Bernward Klocke; Martin Seifert; Stefanie M Hauck; Helmut Laumen; Huan Zhang; Mikael Benson
Journal:  Cell Rep       Date:  2016-06-23       Impact factor: 9.423

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