Gene signature fingerprints stratify SLE patients in groups with similar biological disease profiles: a multicentre longitudinal study - Wahadat, M Javad; Schonenberg-Meinema, Dieneke; van Helden-Meeuwsen, Cornelia G; van Tilburg, Sander J; Groot, Noortje; Schatorjé, Ellen J H; Hoppenreijs, Esther P A H; Hissink Muller, Petra C E; Brinkman, Danielle M C; Dvorak, Denis; Verkaaik, Marleen; van den Berg, J Merlijn; et al. (Rheumatology (Oxford, England), 2022)
OBJECTIVES: Clinical phenotyping and predicting treatment responses in SLE patients is challenging. Extensive blood transcriptional profiling has identified various gene modules that are promising for stratification of SLE patients. We aimed to translate existing transcriptomic data into simpler gene signatures suitable for daily clinical practice. METHODS: Real-time PCR of multiple genes from the IFN M1.2, IFN M5.12, neutrophil (NPh) and plasma cell (PLC) modules, followed by a principle component analysis, was used to identify indicator genes per gene signature. Gene signatures were measured in longitudinal samples from two childhood-onset SLE cohorts (n = 101 and n = 34, respectively), and associations with clinical features were assessed. Disease activity was measured using Safety of Estrogen in Lupus National Assessment (SELENA)-SLEDAI. Cluster analysis subdivided patients into three mutually exclusive fingerprint-groups termed (1) all-signatures-low, (2) only IFN high (M1.2 and/or M5.12) and (3) high NPh and/or PLC. RESULTS: All gene signatures were significantly associated with disease activity in cross-sectionally collected samples. The PLC-signature showed the highest association with disease activity. Interestingly, in longitudinally collected samples, the PLC-signature was associated with disease activity and showed a decrease over time. When patients were divided into fingerprints, the highest disease activity was observed in the high NPh and/or PLC group. The lowest disease activity was observed in the all-signatures-low group. The same distribution was reproduced in samples from an independent SLE cohort. CONCLUSIONS: The identified gene signatures were associated with disease activity and were indicated to be suitable tools for stratifying SLE patients into groups with similar activated immune pathways that may guide future treatment choices.
Keywords: systémový lupus erythematodes; dítě; disease activity; childhood-onset SLE; genové regulační sítě; longitudinální studie; gene signatures; shluková analýza; lidé; clustering analysis; plasma cells; interferon; Gene Regulatory Networks; Lupus Erythematosus, Systemic; transkriptom; Child; neutrophils; biomarkers; Transcriptome; Cluster Analysis; Longitudinal Studies; Humans