Abstract
Hereditary bronchiectasis comprises a group of rare monogenic disorders, with cystic fibrosis (CF) and primary ciliary dyskinesia (PCD) representing the major subtypes. Exome sequencing (ES) remains a central modality for molecular diagnosis; however, it leaves more than half of clinically suspected cases unresolved, largely because it cannot reliably detect copy number variations, deep intronic variants, pseudogene-associated variants, and frequent identification of variants of uncertain significance (VUS). This case series describes five hereditary bronchiectasis cases with initial ES-negative results or VUS findings, illustrating the diagnostic utility of targeted genetic approaches. Systematic re-evaluation-including updated bioinformatic pipelines, familial segregation analyses, genome sequencing, RNA sequencing, and functional assays-such as minigene analysis-enabled the reclassification of VUS and the identification of pathogenic variants, leading to definitive diagnoses of PCD or CF in all individuals. Our findings demonstrate that a multimodal strategy integrating ES reanalysis, advanced genomic technologies, and functional validation is critical for resolving previously undiagnosed cases. Furthermore, emerging multiomics integration, artificial intelligence-driven variant interpretation, and global data-sharing frameworks are positioned to further increase diagnostic precision and support the development of targeted therapies for hereditary bronchiectasis.