Screening patients with autoimmune endocrine disorders for cytokine autoantibodies reveals monogenic immune deficiencies.
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Sjøgren T, Bratland E, Røyrvik EC, Grytaas MA, Benneche A, Knappskog PM, Kämpe O, Oftedal BE, Husebye ES, Wolff ASB
J. Autoimmun. 133 (-) 102917 [2022-12-00; online 2022-09-30]
Autoantibodies against type I interferons (IFN) alpha (α) and omega (ω), and interleukins (IL) 17 and 22 are a hallmark of autoimmune polyendocrine syndrome type 1 (APS-1), caused by mutations in the autoimmune regulator (AIRE) gene. Such antibodies are also seen in a number of monogenic immunodeficiencies. To determine whether screening for cytokine autoantibodies (anti-IFN-ω and anti-IL22) can be used to identify patients with monogenic immune disorders. A novel ELISA assay was employed to measure IL22 autoantibodies in 675 patients with autoimmune primary adrenal insufficiency (PAI) and a radio immune assay (RIA) was used to measure autoantibodies against IFN-ω in 1778 patients with a variety of endocrine diseases, mostly of autoimmune aetiology. Positive cases were sequenced for all coding exons of the AIRE gene. If no AIRE mutations were found, we applied next generation sequencing (NGS) to search for mutations in immune related genes. We identified 29 patients with autoantibodies against IFN-ω and/or IL22. Of these, four new APS-1 cases with disease-causing variants in AIRE were found. In addition, we identified two patients with pathogenic heterozygous variants in CTLA4 and NFKB2, respectively. Nine rare variants in other immune genes were identified in six patients, although further studies are needed to determine their disease-causing potential. Screening of cytokine autoantibodies can efficiently identify patients with previously unknown monogenic and possible oligogenic causes of autoimmune and immune deficiency diseases. This information is crucial for providing personalised treatment and follow-up of patients and their relatives.
Bioinformatics Support for Computational Resources [Service]
NGI Stockholm (Genomics Production) [Service]
National Genomics Infrastructure [Service]
PubMed 36191466
DOI 10.1016/j.jaut.2022.102917
Crossref 10.1016/j.jaut.2022.102917
pii: S0896-8411(22)00125-1