Ozden Sanal, Amy P. Hsu, Steven M. Holland, Barbara Pietrucha, Maria Cristina Pietrogrande, Sara Sebnem Kilic, Mario Perro, Efrem Eren, Cristina Woellner, Rosa Bacchetta, Jiri Litzman, Tim Niehues, Alessandro Plebani, Teresa Espanol, E. Graham Davies, Jukka S. Moilanen, E. Michael Gertz, Bodo Grimbacher, Mehdi Yeganeh, Stephan Ehl, M. Lagos, Peter D. Arkwright, Andrew J. Cant, Stuart E. Turvey, Berta Sánchez, Ben Zion Garty, Mostafa Moin, Fausto Cossu, Alexandra F. Freeman, Mario Abinun, László Maródi, Lennart Hammarström, Caterina Cancrini, José Luis Franco, Dorothee Viemann, Joie Davis, Núria Matamoros, Ulrich Baumann, Edyta Heropolitańska-Pliszka, Erik-Oliver Glocker, Anna Bręborowicz, Anne K. Junker, Alejandro A. Schäffer, Jennifer M. Puck, Claudio Pignata, Andrew R. Gennery, Sujoy Khan, Uludağ Üniversitesi/Tıp Fakültesi/Çocuk Sağlığı ve Hastalıkları Anabilim Dalı., Kılıç, Sara Şebnem, AAH-1658-2021, and Çocuk Sağlığı ve Hastalıkları
Background: The hyper-IgE syndrome (HIES) is a primary immunodeficiency characterized by infections of the lung and skin, elevated serum IgE, and involvement of the soft and bony tissues. Recently, HIES has been associated with heterozygous dominant-negative mutations in the signal transducer and activator of transcription 3 (STAT-3) and severe reductions of T(H)17 cells. Objective: To determine whether there is a correlation between the genotype and the phenotype of patients with HIES and to establish diagnostic criteria to distinguish between STAT3 mutated and STAT3 wild-type patients. Methods: We collected clinical data, determined T(H)17 cell numbers, and sequenced STAT3 in 100 patients with a strong clinical suspicion of HIES and serum IgE > 1000 IU/mL. We explored diagnostic criteria by using a machine-learning approach to identify which features best predict a STAT3 mutation. Results: In 64 patients, we identified 31 different STAT3 mutations, 18 of which were novel. These included mutations at splice sites and outside the previously implicated DNA-binding and Src homology 2 domains. A combination of 5 clinical features predicted STAT3 mutations with 85% accuracy. T(H)17 cells were profoundly reduced in patients harboring STAT-3 mutations, whereas 10 of 13 patients without mutations had low (1000IU/mL plus a weighted score of clinical features >30 based on recurrent pneumonia, newborn rash, pathologic bone fractures, characteristic face, and high palate. Probable: These characteristics plus lack of T(H)17 cells or a family history for definitive HIES. Definitive: These characteristics plus a dominant-negative heterozygous mutation in STAT3. GlaxoSmithKline European consortium (EURO-PADnet HEALRH-F2-2008-201549) Brescia United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Library of Medicine (NLM) United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute of Allergy & Infectious Diseases (NIAID) United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Cancer Institute (NCI) (N01-CO-1240) MEXT-CT-2006-042316 OTKA49017 Fondazione Telethon United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute of Allergy & Infectious Diseases (NIAID) (ZIAAI000646) United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Library of Medicine (NLM) (ZIALM000097)