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.