Variable immunodeficiency study: Evaluation of two European cohorts within a variety of clinical phenotypes

Given the wide heterogeneity of common variable immunodeficiency (CVID), several groups have proposed clinical and immunological classifications to better define follow-up and prognostic algorithms. The present study aims to validate recent clinical and laboratory algorithms, based on different combinations of CVID biomarkers, to provide more personalized treatment and follow-up strategies.

We analysed clinical and immunological features of 80 patients with suspected or diagnosed CVID, in two reference centres of Portugal and Spain. Clinical manifestations were categorized into clinical phenotyping proposed by Chapel et al. [1] that included cytopenia; polyclonal lymphocytic infiltration; unexplained enteropathy; and no disease-related complications.

76% of patients in our cohort entered one of the four categories of clinical phenotyping, without overlap (cytopenia; polyclonal lymphocytic infiltration; unexplained enteropathy; and no disease-related complications). The most prominent phenotype was "cytopenia" (40%) followed by "polyclonal lymphocytic infiltration" (19%). The remaining 24% patients of our cohort had overlap of 2 clinical phenotypes (cytopenia and unexplained enteropathy mainly). A delay of CVID diagnosis in more than 6 years presented 3.7-fold higher risk of developing lymphoproliferation and/or malignancy (p < 0.05), and was associated with increased CD8⁺CD45RO ⁺ T-lymphocytes (p < 0.05). An association between decreased switched-memory B cells with lymphoproliferation and malignancy was observed (p < 0.03 and p < 0.05, respectively). CD4 ⁺ T-lymphocytopenia correlated with autoimmune phenotype, with 30% prevalence (p < 0.05). HLA-DR7 expression was related to CVID onset in early life in our patients (13 vs 25 years), and DQ2.5 or DQ2.2 with unexplained enteropathy (p < 0.05).

The phenotypic and genetic study is crucial for an adequate clinical orientation of CVID patients. In these two independent cohorts of patients, classification based in clinical and laboratory algorithms, provides more personalized treatment and follow-up strategies.