The Immune Deficiency and Dysregulation Activity (IDDA2.1 'Kaleidoscope') Score and Other Clinical Measures in Inborn Errors of Immunity.

ABSTRACT

Quantifying the phenotypic features of rare diseases such as inborn errors of immunity (IEI) helps clinicians make diagnoses, classify disorders, and objectify the disease severity at its first presentation as well as during therapy and follow-up. Furthermore, it may allow cross-sectional and cohort comparisons and support treatment decisions such as an evaluation for transplantation. On the basis of a literature review, we provide a descriptive comparison of ten selected scores and measures frequently used in IEI and divide these into three categories (1) diagnostic tools (for Hyper-IgE syndrome, hemophagocytic lymphohistiocytosis, and Wiskott-Aldrich syndrome), (2) morbidity and disease activity measures (for common variable immune deficiency [CVID], profound combined immune deficiency, CTLA-4 haploinsufficiency, immune deficiency and dysregulation activity [IDDA], IPEX organ impairment, and the autoinflammatory disease activity index), and (3) treatment stratification scores (shown for hypogammaglobulinemia). The depth of preclinical and statistical validations varies among the presented tools, and disease-inherent and user-dependent factors complicate their broader application. To support a comparable, standardized evaluation for prospective monitoring of diseases with immune dysregulation, we propose the IDDA2.1 score (comprising 22 parameters on a 2-5-step scale) as a simple yet comprehensive and powerful tool. Originally developed for use in a retrospective study in LRBA deficiency, this new version may be applied to all IEI with immune dysregulation. Reviewing published aggregate cohort data from hundreds of patients, the IDDA kaleidoscope function is presented for 18 exemplary IEI as an instructive phenotype-pattern visualization tool, and an unsupervised, hierarchically clustered heatmap mathematically confirms similarities and differences in their phenotype expression profiles.