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Published on: March 5, 2019
Flow cytometry optimizing the diagnostic approach in inborn errors of immunity: experience from Egypt
Safa Meshaal1, Rabab Ei Hawary2, Alia Eldash2
1Clinical and Chemical Pathology Department, Faculty of Medicine, Cairo University, Cairo, 11562, Egypt. safa.meshaal@kasralainy.edu.eg.
Summary
Flow cytometry (FCM) effectively screens, categorizes, and monitors patients with inborn errors of immunity (IEI). This cost-effective method significantly improves IEI diagnosis, especially in high-prevalence areas with limited resources.
Area of Science:
- Immunology
- Genetics
- Pediatrics
Background:
- Inborn errors of immunity (IEI) are genetic disorders causing immune system dysfunction, leading to infections, autoimmunity, and malignancies.
- IEI are often autosomal recessive, more prevalent in consanguineous populations, and diagnosis relies on genetic analysis, which isn't always accessible.
- Flow cytometry (FCM) offers a potential diagnostic and monitoring tool for IEI.
Purpose of the Study:
- To report on various IEI categories.
- To assess the impact of expanded flow cytometry (FCM) use in diagnosing, categorizing, and following IEI patients.
- To evaluate FCM utility in a highly consanguineous population.
Main Methods:
- Retrospective chart review of IEI cases diagnosed between 2011 and 2021.
- Focus on cases diagnosed at Cairo University Specialized Pediatric hospital's primary immunodeficiency center.
- Utilized expanded flow cytometry (FCM) for diagnosis and categorization.
Main Results:
- 1510 IEI patients were diagnosed; 1019 with non-genetic disorders.
- Phagocytic defects (30%), severe combined immunodeficiency (22%), and combined immunodeficiency (18.3%) were most common.
- Flow cytometry (FCM) accurately diagnosed and categorized 73% of cases.
Conclusions:
- Multi-color FCM is a cost-effective method for screening, categorizing, and following IEI patients.
- FCM significantly enhances IEI diagnosis when tests are well-designed and targeted.
- This study highlights a decade of IEI diagnosis using FCM in a resource-limited, high-prevalence setting.
