BACKGROUND: The heterogeneity of primary and secondary immunodeficiencies demands for the development of a comprehensive flow cytometric screening system, based on reference values that support a standardized immunophenotypic characterization of most lymphocyte subpopulations. METHODS: Peripheral blood samples from healthy adult volunteers (n = 25) were collected and split into eight panel fractions (100 µl each). Subsequently, premixed eight-color antibody cocktails were incubated per specific panel of whole blood to detect and differentiate cell subsets of: (i) a general lymphocyte overviews, (ii) B-cell subpopulations, (iii) CD4+ subpopulations, (iv) CD8+ subpopulations, (v) regulatory T-cells, (vi) recent thymic emigrants (RTE), (vii) NK-cell subpopulations, and (viii) NK-cell activation markers. All samples were lysed, washed, and measured by flow cytometry. FACS DIVA software was used for data analysis and calculation of quadrant statistics (mean values, standard error of mean, and percentile ranges). RESULTS: Whole blood staining of lymphocytes provided the analysis of: (i) CD3+, 4+, 8+, 19+, 16/56+, and activated CD4/8 cells; (ii) immature, naïve, nonswitched/switched, memory, (activated) CD21(low) , transitional B-cells, plasmablasts/plasmacells; (iii and iv) naïve, central memory, effector, effector memory, TH1/TH2/TH17-like, and CCR5+CD8-cells; (v) CD25+, regulatory T-cells (naïve/memory, HLA-DR+); (vi) α/β- and γ/δ-T-cells, RTE in CD4/CD8 cells; (vii) immature/mature CD56(bright) , CD94/NKG2D+ NK-cells; and (viii) Nkp30, 44, 46, and CD57+NK-cells. Clinical examples and quadrant statistics are provided. CONCLUSION: The present study represents a practical approach to standardize the immunophenotyping of most T-, B-, and NK-cell subpopulations. That allows differentiating whether abnormalities or developmental shifts observed in lymphocyte subpopulations originates either from primary or secondary immunological disturbance.
BACKGROUND: The heterogeneity of primary and secondary immunodeficiencies demands for the development of a comprehensive flow cytometric screening system, based on reference values that support a standardized immunophenotypic characterization of most lymphocyte subpopulations. METHODS: Peripheral blood samples from healthy adult volunteers (n = 25) were collected and split into eight panel fractions (100 µl each). Subsequently, premixed eight-color antibody cocktails were incubated per specific panel of whole blood to detect and differentiate cell subsets of: (i) a general lymphocyte overviews, (ii) B-cell subpopulations, (iii) CD4+ subpopulations, (iv) CD8+ subpopulations, (v) regulatory T-cells, (vi) recent thymic emigrants (RTE), (vii) NK-cell subpopulations, and (viii) NK-cell activation markers. All samples were lysed, washed, and measured by flow cytometry. FACS DIVA software was used for data analysis and calculation of quadrant statistics (mean values, standard error of mean, and percentile ranges). RESULTS: Whole blood staining of lymphocytes provided the analysis of: (i) CD3+, 4+, 8+, 19+, 16/56+, and activated CD4/8 cells; (ii) immature, naïve, nonswitched/switched, memory, (activated) CD21(low) , transitional B-cells, plasmablasts/plasmacells; (iii and iv) naïve, central memory, effector, effector memory, TH1/TH2/TH17-like, and CCR5+CD8-cells; (v) CD25+, regulatory T-cells (naïve/memory, HLA-DR+); (vi) α/β- and γ/δ-T-cells, RTE in CD4/CD8 cells; (vii) immature/mature CD56(bright) , CD94/NKG2D+ NK-cells; and (viii) Nkp30, 44, 46, and CD57+NK-cells. Clinical examples and quadrant statistics are provided. CONCLUSION: The present study represents a practical approach to standardize the immunophenotyping of most T-, B-, and NK-cell subpopulations. That allows differentiating whether abnormalities or developmental shifts observed in lymphocyte subpopulations originates either from primary or secondary immunological disturbance.
Authors: Anna K Haugaard; Hanne V Marquart; Lilian Kolte; Lars Peter Ryder; Michala Kehrer; Maria Krogstrup; Ulrik B Dragsted; Benny Dahl; Ida E Gjørup; Åse B Andersen; Peter Garred; Susanne D Nielsen Journal: Sci Rep Date: 2018-10-11 Impact factor: 4.379
Authors: Jacques J M van Dongen; Mirjam van der Burg; Tomas Kalina; Martin Perez-Andres; Ester Mejstrikova; Marcela Vlkova; Eduardo Lopez-Granados; Marjolein Wentink; Anne-Kathrin Kienzler; Jan Philippé; Ana E Sousa; Menno C van Zelm; Elena Blanco; Alberto Orfao Journal: Front Immunol Date: 2019-06-13 Impact factor: 7.561
Authors: José C Jaime-Pérez; César D Villarreal-Villarreal; Eduardo Vázquez-Garza; Nereida Méndez-Ramírez; Rosario Salazar-Riojas; David Gómez-Almaguer Journal: Data Brief Date: 2016-03-31
Authors: Vanesa Cunill; Margarita Massot; Antonio Clemente; Carmen Calles; Valero Andreu; Vanessa Núñez; Antonio López-Gómez; Rosa María Díaz; María de Los Reyes Jiménez; Jaime Pons; Cristòfol Vives-Bauzà; Joana Maria Ferrer Journal: Front Immunol Date: 2018-05-29 Impact factor: 7.561