B Lymphocytes, Autoimmunity and Immunotherapies, UMR 1227, Univ Brest, Inserm, Brest 29200, France.
Brest University Hospital, Brest 29200, France.
Database (Oxford). 2024 May 28;2024. doi: 10.1093/database/baae045.
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.
在系统性红斑狼疮 (SLE) 等复杂自身免疫性疾病领域,系统免疫学方法在转化研究中已被证明具有重要价值。已经收集了大量的转录组谱数据集,并在公共存储库中提供给研究界,但主流研究人员仍然难以访问和使用这些数据。能够促进研究人员与大规模数据集交互的工具和技术,如用户友好的 Web 应用程序,可以促进数据重用和促进知识发现。使用第三代 (BloodGen3) 模块框架对 LUPUCE 队列的微阵列血液转录组数据(可在基因表达综合数据库 [GSE49454] 上公开获得)进行了分析,该框架由模块和模块聚合体组成。这些特征良好的样本对应于不同程度的疾病活动、不同类型的发作(包括经活检证实的狼疮性肾炎)、不同的自身抗体谱和不同水平的干扰素特征。部署了一个 Web 应用程序来呈现 LUPUCE 数据集的聚合水平、模块水平和基因水平分析结果。用户可以探索 SLE 样本的相似性和异质性,浏览不同的分析水平,检验假设并生成自定义指纹网格和热图,这些可以用于报告或手稿。该资源可通过以下链接获得:https://immunology-research.shinyapps.io/LUPUCE/。该 Web 应用程序可用作独立资源,用于探索 SLE 患者血液转录谱的变化及其与临床和免疫学参数的关系,以生成新的研究假设。