Whole Genome Sequencing in 25 Families with Suspected Inborn Errors of Immunity: Diagnostic Yield and Clinical Relevance of Genome-wide Analysis

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J Clin Immunol. 2025 Nov 23. doi: 10.1007/s10875-025-01947-2. Online ahead of print.

ABSTRACT

INTRODUCTION: Inborn errors of immunity (IEIs) constitute a diverse group of more than 500 disorders resulting from pathogenic variants in over 500 causative genes, with most being monogenic diseases. The use of exome sequencing based on next-generation sequencing technologies has significantly advanced the discovery of causative variants underlying IEIs and has achieved diagnostic yields of up to 40%. Despite these advances, a substantial proportion of patients still remain genetically undiagnosed due to limitations in detecting deep intronic or structural variants. Accordingly, we applied whole-genome sequencing to a cohort of patients suspected of IEIs in order to evaluate its diagnostic yield and capacity to identify novel structural genomic alterations.

METHODS: We analyzed data from 25 probands presenting with suspected IEIs based on clinical features, who were enrolled through the National Bio-Big Data Program’s whole genome sequencing (WGS) project at Samsung Medical Center, spanning July 2020 to February 2022. The study utilized a stepwise analytical protocol involving initial candidate gene panel analysis for detecting small variants, subsequent investigation of structural variants, and then a genotype-driven approach utilizing in-house bioinformatics pipelines. All identified variants were assessed for pathogenicity in accordance with the 2015 ACMG/AMP guidelines for the interpretation of sequence variants.

RESULTS: Causative variants were detected in 10 (40%) probands using candidate gene panel analysis, which included BTK, CYBB, DKC1, DNAH11, DNAH5, IL2RG, NFKB2, PIK3CD and SH2D1A. Genotype-driven analysis identified pathogenic variants in two (8%) probands involving NF1 and PTPN11, while an additional five (20%) probands were found to have structural variants, including BTK, LRBA and SH2D1A. In total, genetic analysis revealed causative variants in 60% of patients. Variants of uncertain significance were identified in four cases among three probands (12%).

CONCLUSION: WGS facilitated the robust identification of causative genetic variants, including complex structural changes. These results suggest that employing WGS in patients suspected of IEIs could provide additional diagnostic yield.

PMID:41275043 | DOI:10.1007/s10875-025-01947-2

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