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Rapid Flow Cytometry-Based Test for the Diagnosis of Lipopolysaccharide Responsive Beige-Like Anchor (LRBA) Deficiency

Overview of attention for article published in Frontiers in immunology, April 2018
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Title
Rapid Flow Cytometry-Based Test for the Diagnosis of Lipopolysaccharide Responsive Beige-Like Anchor (LRBA) Deficiency
Published in
Frontiers in immunology, April 2018
DOI 10.3389/fimmu.2018.00720
Pubmed ID
Authors

Laura Gámez-Díaz, Elena C. Sigmund, Veronika Reiser, Werner Vach, Sophie Jung, Bodo Grimbacher

Abstract

The diagnosis of lipopolysaccharide-responsive beige-like-anchor-protein (LRBA) deficiency currently relies on gene sequencing approaches that do not support a timely diagnosis and clinical management. We developed a rapid and sensitive test for clinical implementation based on the detection of LRBA protein by flow cytometry in peripheral blood cells after stimulation. LRBA protein was assessed in a prospective cohort of 54 healthy donors and 57 patients suspected of LRBA deficiency. Receiver operating characteristics analysis suggested an LRBA:MFI ratio cutoff point of 2.6 to identify LRBA-deficient patients by FACS with 94% sensitivity and 80% specificity and to discriminate them from patients with a similar clinical picture but other disease-causing mutations. This easy flow cytometry-based assay allows a fast screening of patients with suspicion of LRBA deficiency reducing therefore the number of patients requiring LRBA sequencing and accelerating the treatment implementation. Detection of biallelic mutations in LRBA is however required for a definitive diagnosis.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 21%
Researcher 6 18%
Student > Doctoral Student 4 12%
Student > Ph. D. Student 2 6%
Other 1 3%
Other 2 6%
Unknown 12 35%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 26%
Immunology and Microbiology 7 21%
Medicine and Dentistry 4 12%
Agricultural and Biological Sciences 2 6%
Unknown 12 35%