Investigating effective filter criteria for functional variant discovery of inborn errors of immunity in whole exome sequencing data

Abstract

This proposal aims to enhance the discovery of disease-causing variants in whole exome sequencing data from undiagnosed patients, addressing existing analytical challenges and proposing a standardized pipeline for increased discovery of new inborn errors of immunity (IEIs). Currently, the International Union of Immunological Societies (IUIS) Expert Committee recognizes only 485 IEIs. These IEIs are utilized as gene panels for variant detection in new patients. However, only 46% of severe immune response cases are diagnosed through Next Generation Sequencing (NGS), indicating that there are still unknown IEIs. The diverse criteria used in current NGS analysis pipelines, coupled with the absence of a universal standard, underscores the need for a standardized approach. The proposed pipeline utilizes data from GTEx, gnomAD, and dbSNP, employing an incorporated and sequential filtering process at allele, gene, and protein levels. This prioritizes variants by allele-specific filtering based on quality, location, MAF, CADD score, mutation type, and coverage, followed by gene-specific criteria, such as expression and conservation, and concludes with variant effect prediction to assess the functionality of the protein with the given variant. By prioritizing variants according to predefined criteria, this pipeline offers the potential to uncover new IEIs, allowing the in-depth characterization of the mechanisms of immune diseases and facilitating accurate diagnosis and treatment for patients.