Document Type
Article
Publication Date
5-28-2024
Original Citation
Bettacchioli E,
Chiche L,
Chaussabel D,
Cornec D,
Jourde-Chiche N,
Rinchai D.
An interactive web application for exploring systemic lupus erythematosus blood transcriptomic diversity. Database (Oxford). 2024;2024.
Keywords
JGM, Lupus Erythematosus, Systemic, Humans, Transcriptome, Internet, Databases, Genetic, Gene Expression Profiling, Software
JAX Source
Database (Oxford). 2024;2024.
ISSN
1758-0463
PMID
38805754
DOI
https://doi.org/10.1093/database/baae045
Grant
The LUPUCE study (ClinicalTrials.gov identifier: NCT00920114) was supported by the Appel d’Offres de Recherche Clinique–Assistance Publique Hôpitaux de Mar- seille (APHM) (AORC 2008 2009–04); the Association pour le Développement des Recherches Biologiques et Médicales, the Centre de Recherche en Néphrologie (La Conception, Marseille); the National Institute of Allergy and Infectious Diseases, Autoimmunity Centers of Excellence grant (U19- AI-082715). Open Access funding provided by the Qatar National Library.
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.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.