Key result
Multidimensional phenomapping identifies 3 distinct clinical-immunological clusters in recurrent pericarditis.
Why the study?
Phenotype-oriented management is increasingly advocated in recurrent pericarditis, but it remains unclear whether clinically recognizable phenotypes reflect underlying disease biology or are shaped by current inflammation and treatment exposure.
Does multidimensional phenomapping identify discrete biological endotypes versus treatment- and inflammation-shaped states in patients with idiopathic recurrent pericarditis?
Cohort (n=101)
Yes
Does multidimensional phenomapping identify discrete biological endotypes versus treatment- and inflammation-shaped states in patients with idiopathic recurrent pericarditis?
Phenotypic heterogeneity in idiopathic recurrent pericarditis reflects a dynamic spectrum shaped by inflammatory state and treatment exposure rather than discrete stable endotypes, though anti-IL-1Ra autoantibodies mark a consistent active inflammatory signature.
Answers are grounded in this paper and cite their sources.
Phenomapping may delineate RP subtypes; leaves open whether clusters reflect biology or treatment exposure.
BACKGROUND: Phenotype-oriented management is increasingly advocated in recurrent pericarditis (RP), but it remains unclear whether clinically recognizable phenotypes reflect underlying disease biology or are shaped by current inflammation and treatment exposure. We used multidimensional phenomapping to investigate this heterogeneity. METHODS: We analysed 101 patients with idiopathic RP from the multicenter PERIPLO cohort. Factor analysis of mixed data followed by hierarchical clustering defined the index solution. Robustness was assessed across alternative specifications and models excluding treatment, inflammatory state or the IL-1Ra axis. RESULTS: Three clinical-immunological patterns emerged: a predominantly remission-state, anakinra-treated group; a predominantly remission-state group largely managed without IL-1 blockade; and an active inflammatory group enriched for anti-IL-1Ra autoantibodies and characterized by markedly reduced measured IL-1Ra. The two antibody-negative groups were extensively reorganized after treatment variables were removed, whereas exclusion of the IL-1Ra axis nearly abolished agreement with the original partition. In contrast, anti-IL-1Ra positivity remained consistently associated with active inflammation and very low measured IL-1Ra. CONCLUSIONS: In this cohort, the phenotypic heterogeneity of RP was better represented as a clinical-immunological spectrum shaped by inflammatory state and treatment exposure than as discrete, stable endotypes. The anti-IL-1Ra-associated inflammatory signature was the most internally consistent biological signal. These exploratory findings require external validation, and longitudinal multidimensional phenomapping should test whether this signature can inform patient management.
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Wu et al. (2026) conducted a cohort in Idiopathic recurrent pericarditis (n=101). Multidimensional phenomapping (factor analysis of mixed data and hierarchical clustering) vs. Alternative model specifications excluding treatment, inflammatory state, or the IL-1Ra axis was evaluated on Clinical-immunological phenotypic patterns (clusters). Multidimensional phenomapping in 101 recurrent pericarditis patients identified 3 clinical-immunological patterns shaped by inflammation, treatment, and anti-IL-1Ra autoantibodies.
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