Background Hyper-IgE Syndrome (HIES) is a rare, autosomal dominant (AD) immunodeficiency characterized by eczema, Staphylococcus aureus skin abscesses, pneumonia with pneumatocele formation, Candida infections, and skeletal/connective tissue abnormalities. Recently it was shown that heterozygous STAT3 mutations cause AD-HIES. Objective To determine the spectrum and functional consequences of heterozygous STAT3 mutations in a cohort of HIES patients. Methods We sequenced the STAT3 gene in 38 HIES patients (NIH-score >40 points) from 35 families, quantified TH17 cells in peripheral blood, and evaluated tyrosine phosphorylation of STAT3. Results Most STAT3 mutations in our cohort were in the DNA-binding domain (DBD) (22/35 families) or SH2 domain (10/35), and were missense mutations. We identified two intronic mutations resulting in exon skipping and in-frame deletions within the DBD. In addition, we identified two mutations located in the transactivation domain downstream of the SH2 domain: A ten amino acid deletion and an amino acid substitution. In one patient, we were unable to identify a STAT3 mutation. TH17 cells were absent or low in the peripheral blood of all patients who were evaluated (n=17). IL-6 induced STAT3-phosphorylation was consistently reduced in patients with SH2 domain mutations, but comparable to normal controls in patients with mutations in the DBD. Conclusion Heterozygous STAT3 mutations were identified in 34/35 unrelated HIES families. Patients had impaired TH17 cell development, and those with SH2 domain mutations had reduced STAT3 phosphorylation. Clinical implication Mutations in STAT3 and decreased TH17 cells identify individuals with AD-HIES, thereby allowing timely diagnosis and early treatment of these patients. Capsule summary Results from this patient cohort expand the spectrum of heterozygous STAT3 mutations in AD-HIES, and demonstrate impaired development of TH17 cells in all and reduced STAT3-phosphorylation in patients with SH2-domain mutations.

Autoantibodies have been associated with autoimmune diseases. However, studies have identified autoantibodies in healthy donors (HD) who do not develop autoimmune disorders. Here we provide evidence of a network of immunoglobulin G (IgG) autoantibodies targeting G protein-coupled receptors (GPCR) in HD compared to patients with systemic sclerosis, Alzheimer’s disease, and ovarian cancer. Sex, age and pathological conditions affect autoantibody correlation and hierarchical clustering signatures, yet many of the correlations are shared across all groups, indicating alterations to homeostasis. Furthermore, we identify relationships between autoantibodies targeting structurally and functionally related molecules, such as vascular, neuronal or chemokine receptors. Finally, autoantibodies targeting the endothelin receptor type A (EDNRA) exhibit chemotactic activity, as demonstrated by neutrophil migration toward HD-IgG in an EDNRA-dependent manner and in the direction of IgG from EDNRA-immunized mice. Our data characterizing the in vivo signatures of anti-GPCR autoantibodies thus suggest that they are a physiological part of the immune system.

No abstract

The majority of Latin American CGD patients carry a hemizygous mutation in the CYBB gene. They also presented a wide range of clinical manifestations most frequently bacterial and fungal infections of the respiratory tract, skin, and lymph nodes. Thirty percent of the Latin American CGD patients presented adverse reactions to BCG, indicating that this vaccine should be avoided in these patients.

COVID-19 shares the feature of autoantibody production with systemic autoimmune diseases. In order to understand the role of these immune globulins in the pathogenesis of the disease, it is important to explore the autoantibody spectra. Here we show, by a cross-sectional study of 246 individuals, that autoantibodies targeting G protein-coupled receptors (GPCR) and RAS-related molecules associate with the clinical severity of COVID-19. Patients with moderate and severe disease are characterized by higher autoantibody levels than healthy controls and those with mild COVID-19 disease. Among the anti-GPCR autoantibodies, machine learning classification identifies the chemokine receptor CXCR3 and the RAS-related molecule AGTR1 as targets for antibodies with the strongest association to disease severity. Besides antibody levels, autoantibody network signatures are also changing in patients with intermediate or high disease severity. Although our current and previous studies identify anti-GPCR antibodies as natural components of human biology, their production is deregulated in COVID-19 and their level and pattern alterations might predict COVID-19 disease severity.