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An interactive web application for exploring systemic lupus erythematosus blood transcriptomic diversity.
Bettacchioli, Eléonore; Chiche, Laurent; Chaussabel, Damien; Cornec, Divi; Jourde-Chiche, Noémie; Rinchai, Darawan.
Affiliation
  • Bettacchioli E; B Lymphocytes, Autoimmunity and Immunotherapies, UMR 1227, Univ Brest, Inserm, Brest 29200, France.
  • Chiche L; Brest University Hospital, Brest 29200, France.
  • Chaussabel D; Department of Internal Medicine, Hôpital Européen, Marseille 13003, France.
  • Cornec D; Translational Medicine Division, Research Branch, Sidra Medicine, Doha 26999, Qatar.
  • Jourde-Chiche N; Computational Sciences Department, The Jackson Laboratory, Farmington, CT 06032, USA.
  • Rinchai D; B Lymphocytes, Autoimmunity and Immunotherapies, UMR 1227, Univ Brest, Inserm, Brest 29200, France.
Database (Oxford) ; 20242024 May 28.
Article in En | MEDLINE | ID: mdl-38805754
ABSTRACT
In the field of complex autoimmune diseases such as systemic lupus erythematosus (SLE), systems immunology approaches have proven invaluable in translational research settings. Large-scale datasets of transcriptome profiling have been collected and made available to the research community in public repositories, but remain poorly accessible and usable by mainstream researchers. Enabling tools and technologies facilitating investigators' interaction with large-scale datasets such as user-friendly web applications could promote data reuse and foster knowledge discovery. Microarray blood transcriptomic data from the LUPUCE cohort (publicly available on Gene Expression Omnibus, GSE49454), which comprised 157 samples from 62 adult SLE patients, were analyzed with the third-generation (BloodGen3) module repertoire framework, which comprises modules and module aggregates. These well-characterized samples corresponded to different levels of disease activity, different types of flares (including biopsy-proven lupus nephritis), different auto-antibody profiles and different levels of interferon signatures. A web application was deployed to present the aggregate-level, module-level and gene-level analysis results from LUPUCE dataset. Users can explore the similarities and heterogeneity of SLE samples, navigate through different levels of analysis, test hypotheses and generate custom fingerprint grids and heatmaps, which may be used in reports or manuscripts. This resource is available via this link https//immunology-research.shinyapps.io/LUPUCE/. This web application can be employed as a stand-alone resource to explore changes in blood transcript profiles in SLE, and their relation to clinical and immunological parameters, to generate new research hypotheses.
Subject(s)

Full text: 1 Database: MEDLINE Main subject: Transcriptome / Lupus Erythematosus, Systemic Limits: Humans Language: En Year: 2024 Type: Article

Full text: 1 Database: MEDLINE Main subject: Transcriptome / Lupus Erythematosus, Systemic Limits: Humans Language: En Year: 2024 Type: Article