A multidisciplinary RNA-guided approach to complement genomic analysis of unsolved patients with an inborn error of immunity

Introduction: Inborn errors of immunity (IEI) comprise a heterogeneous, and growing, group of over 550 disorders linked to over 500 genes. Current diagnostic rates for IEI range from 15-70%, with missed diagnoses likely explained by variants of uncertain significance that lack evidence for reclassification and/or variants undetectable with current methods. To overcome these limitations, we developed a structured, RNA-guided approach to reanalyze unsolved IEI patients and increase the diagnostic yield of genetic testing. Methods: In a multidisciplinary team, we analyzed a cohort of 22 patients suspected to have an IEI for whom standard diagnostic genetic testing was inconclusive. We systematically evaluated whether aberrant expression, aberrant splicing or mono-allelic expression, based on the detection of expression outliers, splicing outliers and allele-specific read counts at heterozygous single nucleotide variants could reveal potentially causative variants that aligned with the clinical phenotype and expected mode of inheritance. Results: In one male patient, we detected a splice variant in IKBKG (NM_001099857.5: c.671 + 2T>G) that causes exon 5 skipping, which explains his phenotype. In one female patient, we detected a pathogenic splice variant in the X-linked recessive gene CYBB (NM_000397.4: c.45 + 5G>A) that, in combination with skewed X-inactivation, caused a significant decrease in functional transcripts. We also detected a deep-intronic variant (NM_003998.4: c.1495 + 506T>C) that activates a cryptic splice site, leading to a pseudo-exon in NFKB1 in a patient with a phenotype consistent with NFKB1 haploinsufficiency. Conclusion: We could provide a conclusive diagnosis for 2 out of 22 patients, underscoring how RNA-guided variant interpretation can improve genetic diagnostic yield in IEI patients. With advances in interpretation technologies, integrating RNA-sequencing into routine diagnostics could be a pivotal step toward achieving more comprehensive and precise genetic diagnoses of IEI.