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.
Zhou et al. (Sun,) studied this question.