Clinical-Immunological Phenomapping in Recurrent Pericarditis: Disentangling Biological Traits, Inflammatory State and Treatment Exposure.

Authors

M A Wu, C Kessel, R Colombo, S Fuehner, S Berra, A Caforio, A Brucato, L Thurner

Published in

European journal of clinical investigation. Volume 56. Issue 11.

Abstract

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.
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.
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.
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.

PMID:
43001649
Bibliographic data and abstract were imported from PubMed on 09 Nov 2026.

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