Key points are not available for this paper at this time.
Background: Autoimmune diseases involve disruptions in immune tolerance, persistent systemic inflammation, and progressive multi-organ involvement, with increasing global prevalence. Accurate prediction of disease flares and complications, alongside tools for activity stratification, represents a significant clinical challenge. C-reactive protein (CRP), a canonical pattern recognition molecule of the pentraxin family, is a widely employed inflammatory biomarker; however, its expression patterns, cellular origins, and disease-specific roles across autoimmune conditions have not been comprehensively assessed. Methods: This study integrated retrospective clinical cohort analyses from Nanjing Drum Tower Hospital with population-level data from the National Health and Nutrition Examination Survey, proteomic profiling, and single-cell RNA sequencing to examine CRP expression across multiple autoimmune diseases, including systemic lupus erythematosus, Sjögren's disease, autoimmune hepatitis, and various inflammatory arthritides. Results: Clinical data indicate that CRP levels exhibit considerable heterogeneity across these conditions. Proteomic analyses identify CRP as a core inflammatory mediator in conditions such as rheumatoid arthritis, while single-cell RNA sequencing delineates its major cellular sources. Integration of population-level data supports these heterogeneous patterns and demonstrates positive correlations between CRP levels and systemic inflammatory burden, as well as associations with hematologic parameters. Additionally, liver-derived single-cell and spatial transcriptomic data offer insights into the tissue-specific inflammatory landscape in autoimmune hepatitis. Conclusions: Collectively, this study maps the CRP expression landscape across multiple autoimmune diseases and identifies cellular sources in specific disease contexts. These findings indicate that CRP interpretation in autoimmune settings requires consideration of both disease type and clinical context, which may inform more refined strategies for early detection and patient stratification.
Yang et al. (Mon,) studied this question.