Common variable immunodeficiency disorder (CVID) is a group of diseases in which the capacity to produce antibodies (immunoglobulins, Igs) against microbial infections is impaired. There is a marked decrease in one or more Ig classes and the number and/or function of certain B lymphocyte subsets may be reduced. In addition to an increased susceptibility to infections, CVID is also associated with auto-immune and malignant conditions. The heterogeneity in both clinical and immunological presentation complicates the elucidation of the underlying disease mechanisms and gene defects. Up to now, a specific genetic cause has only been found in less than 10% of CVID patients.
The general objective of this study is to develop a unique pipeline for classification of CVID patients that integrates clinical data, advanced immunophenotyping, molecular analyses and next-generation sequencing (NGS) in order to discover (new) gene defects. Specifically, clinical an dimmunological data from our CVID patients will be used for classification based on functional blockage in B cell development. From this, class-specific candidate gene lists will be generated using text-mining tools, which well guide and greatly facilitate the analysis of NGS data.
We believe that this unique approach will bring novelty and power to the field of CVID research, and hopefully generate leads for novel therapeutic approaches.