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Title: Flow cytometry-based diagnosis of primary immunodeficiency diseases
Authors: Kanegane, Hirokazu
Hoshino, Akihiro
Okano, Tsubasa
Yasumi, Takahiro  kyouindb  KAKEN_id
Wada, Taizo
Takada, Hidetoshi
Okada, Satoshi
Yamashita, Motoi
Yeh, Tzu-wen
Nishikomori, Ryuta
Takagi, Masatoshi
Imai, Kohsuke
Ochs, Hans D.
Morio, Tomohiro
Author's alias: 八角, 高裕
西小森, 隆太
Keywords: Flow cytometry
Intracellular protein
Monoclonal antibody
Primary immunodeficiency disease
Surface protein
Issue Date: Jan-2018
Publisher: Elsevier BV
Journal title: Allergology International
Volume: 67
Issue: 1
Start page: 43
End page: 54
Abstract: Primary immunodeficiencies (PIDs) are a heterogeneous group of inherited diseases of the immune system. The definite diagnosis of PID is ascertained by genetic analysis; however, this takes time and is costly. Flow cytometry provides a rapid and highly sensitive tool for diagnosis of PIDs. Flow cytometry can evaluate specific cell populations and subpopulations, cell surface, intracellular and intranuclear proteins, biologic effects associated with specific immune defects, and certain functional immune characteristics, each being useful for the diagnosis and evaluation of PIDs. Flow cytometry effectively identifies major forms of PIDs, including severe combined immunodeficiency, X-linked agammaglobulinemia, hyper IgM syndromes, Wiskott-Aldrich syndrome, X-linked lymphoproliferative syndrome, familial hemophagocytic lymphohistiocytosis, autoimmune lymphoproliferative syndrome, IPEX syndrome, CTLA 4 haploinsufficiency and LRBA deficiency, IRAK4 and MyD88 deficiencies, Mendelian susceptibility to mycobacterial disease, chronic mucocuneous candidiasis, and chronic granulomatous disease. While genetic analysis is the definitive approach to establish specific diagnoses of PIDs, flow cytometry provides a tool to effectively evaluate patients with PIDs at relatively low cost.
Rights: © 2017, Japanese Society of Allergology. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (
DOI(Published Version): 10.1016/j.alit.2017.06.003
PubMed ID: 28684198
Appears in Collections:Journal Articles

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