Diagnostic approach to the hyper-IgE syndromes: Immunologic and clinical key findings to differentiate hyper-IgE syndromes from atopic dermatitis

Background: Hyper-IgE syndromes (HIES) are primary immunodeficiency disorders characterized by Staphylococcus aureus abscesses, recurrent pneumonia, increased serum IgE levels, and eczema. The association of heterozygous signal transducer and activator of transcription 3 (STAT3) mutations with autosomal dominant (AD)-HIES allows the differentiation of AD-HIES from disorders associated with eczema and increased serum IgE levels, such as other primary immunodeficiencies and atopic dermatitis. Objective: To facilitate early diagnosis of AD-HIES to initiate appropriate therapy. Methods: The clinical phenotype (suggested by a National Institutes of Health [NIH] score of ≥40 points), STAT3 genotype, and T_H17 cell counts were compared in a cohort of 78 patients suspected of having HIES. Results: Heterozygous STAT3 missense mutations and in-frame deletions were identified in 48 patients, all but 2 with an NIH score ≥40 points. Patients with STAT3 mutations with HIES showed significantly lower T_H17 cell counts compared with patients with wild-type STAT3 and control subjects. Only 1 patient with wild-type STAT3 had both an NIH score ≥40 points and abnormal T_H17 cell counts (≤0.2% of CD4⁺ cells), with this exception being identified with a homozygous dedicator of cytogenesis 8 protein (DOCK8) mutation. Pathologic shedding of primary teeth was present in 3 patients with wild-type STAT3 and 33 patients with STAT3 mutations. Internal abscesses and severe infections were exclusively seen in patients with STAT3 mutations, who also had increased pneumatocele formation and skeletal or connective tissue manifestations compared with patients with wild-type STAT3. Conclusion: We expanded the number of STAT3 mutations and validated that the NIH score sensitively identifies patients with HIES. Based on our patient cohort, we propose key findings that, when combined with T_H17 cell numbers, predict patients with AD-HIES with STAT3 mutations, supporting early diagnosis of AD-HIES.