database for inborn errors of immunity

Background: To date, no publicly accessible platform has captured and synthesized all of the layered dimensions of genotypic, phenotypic, and mechanistic information published in the field of inborn errors of immunity (IEIs). Such a platform would represent the extensive and complex landscape of IEIs and could increase the rate of diagnosis in patients with a suspected IEI, which remains unacceptably low. Objective: Our aim was to create an expertly curated, patientcentered, multidimensional IEI database that enables aggregation and sophisticated data interrogation and promotes involvement from diverse stakeholders across the community. Methods: The database structure was designed following a subject-centered model and written in Structured Query Language (SQL). The web application is written in Hypertext Preprocessor (PHP), Hypertext Markup Language (HTML), Cascading Style Sheets (CSS), and JavaScript. All data stored in the Genetic Immunology Advisor (GenIA) are extracted by manually reviewing published research articles. Results: We completed data collection and curation for 24 pilot genes. Using these data, we have exemplified how GenIA can provide quick access to structured, longitudinal, more thorough, comprehensive, and up-to-date IEI knowledge than do currently existing databases, such as ClinGen, Human Phenotype Ontology (HPO), ClinVar, or Online Mendelian Inheritance in Man (OMIM), with which GenIA intends to dovetail. Conclusions: GenIA strives to accurately capture the extensive genetic, mechanistic, and phenotypic heterogeneity found across IEIs, as well as genetic paradigms and diagnostic pitfalls associated with individual genes and conditions. The IEI community's involvement will help promote GenIA as an enduring resource that supports and improves knowledge sharing, research, diagnosis, and care for patients with genetic immune disease. (J Allergy Clin Immunol 2024;153:831-43.)