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Updated: Jun 17, 2026

Primary Human Nasal Epithelial Cells: Biobanking in the Context of Precision Medicine
Published on: April 22, 2022
Uplift of genetic diagnosis of rare respiratory disease using airway epithelium transcriptome analysis
Jelmer Legebeke1,2, Gabrielle Wheway1,2, Lee Baker1,2,3
1School of Human Development and Health, Institute for Developmental Sciences Building, Tremona Road, Southampton, Hampshire SO16 6YD, United Kingdom.
Abstract:
Rare genetic respiratory disease has an incidence rate of more than 1:2500 live births in Northern Europe and carries significant disease burden. Early diagnosis improves outcomes, but many individuals remain without a confident genetic diagnosis. Improved and expanded molecular testing methods are required to improve genetic diagnosis rates and thereby improve clinical outcomes. Using primary ciliary dyskinesia (PCD) as an exemplar rare genetic respiratory disease, we developed a standardized method to identify pathogenic variants using whole transcriptome RNA-sequencing (RNA-seq) of nasal epithelial cells cultured at air-liquid interface (ALI). The method was optimized using cells from healthy volunteers, and people with rhino-pulmonary disease but no diagnostic indication of PCD. We validated the method using nasal epithelial cells from PCD patients with known genetic cause. We then assessed the ability of RNA-seq to identify pathogenic variants and the disease mechanism in PCD likely patients but in whom DNA genetic testing was inconclusive. The majority of 49 targeted PCD genes were optimally identified in RNA-seq data from nasal epithelial cells grown for 21 days at ALI culture. Four PCD-likely patients without a previous genetic diagnosis received a confirmed genetic diagnosis from the findings of the RNA-seq data. We demonstrate the clinical potential of RNA-seq of nasal epithelial cells to identify variants in individuals with genetically unsolved PCD. This uplifted genetic diagnosis should improve genetic counselling, enables family cascade screening, opens the door to potential personalised treatment and care approaches. This methodology could be implemented in other rare lung diseases such as cystic fibrosis.
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