Primary Immune Deficiency diseases (PIDs) comprise a heterogeneous group of life-threatening inherited disorders of the immune system with clinical heterogeneity and poor genotype-phenotype correlation, making their diagnosis a challenge.

The recent evolutions in genetic testing have led to an exponential increase in the identification of PID-causing gene defects. Nevertheless, an underlying disease-causing gene is detected in only 10- 20% of the PID patients. As a result, a large number of patients remain undiagnosed or remain undefined PID. Beside genetic testing, immunophenotyping using multi-parameter flow cytometry is an important tool in the diagnostic and prognostic work-up of PID. Despites its crucial role, flow cytometric analysis in PID diagnostics is still faced with several challenges (e.g. standardization and reference values are lacking, lack of clinical validation on large datasets, difficult data analysis).
The aim of this project is to clinically validate and optimize the use of standardized multi- parameter immunophenotyping in the context PID as a tool for early diagnosis, risk assessment and personalized treatment. To this end we will apply the standardized Euroflow strategy in a
consecutive patient series with suspicion of PID/known PID diagnosis in two university hospitals in order to make it routinely applicable across different labs in Belgium, and subsequently across Europe. In addition, we will evaluate the clinical added value of using new and automated software tools based on (un)supervised machine learning techniques.