Primary ciliary dyskinesia (PCD) is a genetically heterogeneous recessive disorder caused by several distinct defects in genes responsible for ciliary beating, leading to defective mucociliary clearance often associated with randomization of left/right body asymmetry. Individuals with PCD caused by defective radial spoke (RS) heads are difficult to diagnose owing to lack of gross ultrastructural defects and absence of situs inversus. Thus far, most mutations identified in human radial spoke genes (RSPH) are loss-of-function mutations, and missense variants have been rarely described. We studied the consequences of different RSPH9, RSPH4A, and RSPH1 mutations on the assembly of the RS complex to improve diagnostics in PCD. We report 21 individuals with PCD (16 families) with biallelic mutations in RSPH9, RSPH4A, and RSPH1, including seven novel mutations comprising missense variants, and performed high-resolution immunofluorescence analysis of human respiratory cilia. Missense variants are frequent genetic defects in PCD with RS defects. Absence of RSPH4A due to mutations in RSPH4A results in deficient axonemal assembly of the RS head components RSPH1 and RSPH9. RSPH1 mutant cilia, lacking RSPH1, fail to assemble RSPH9, whereas RSPH9 mutations result in axonemal absence of RSPH9, but do not affect the assembly of the other head proteins, RSPH1 and RSPH4A. Interestingly, our results were identical in individuals carrying loss-of-function mutations, missense variants, or one amino acid deletion. Immunofluorescence analysis can improve diagnosis of PCD in patients with loss-of-function mutations as well as missense variants. RSPH4A is the core protein of the RS head.

Primary ciliary dyskinesia (PCD) is a rare disorder with variable disease progression. To date, mutations in more than 20 different genes have been found. At present, PCD subtypes are described according to the ultrastructural defect on transmission electron microscopy (TEM) of the motile cilia. PCD with normal ultrastructure (NU) is rarely reported because it requires additional testing. Biallelic mutations in DNAH11 have been described as one cause of PCD with NU.

Background Primary ciliary dyskinesia (PCD) is a rare disease, characterised by chronic airway infection. In cystic fibrosis, FEV₁ is insensitive to detect patients with structural damage, and Lung Clearance Index (LCI) was proposed as a better marker of early lung damage. In PCD, the relationship between functional and structural abnormalities has been less studied. We aimed to re-examine this in a cohort of children and adults with mild to moderate PCD. Methods Thirty-eight patients with PCD (5.2–25.0 years) and 70 healthy controls (4.4–25.8 years) were recruited to compare LCI, measured by N₂ multiple breath washout and FEV₁ in a prospective observational trial. In a subset of 30 patients who underwent chest imaging, structural abnormalities were evaluated with cystic fibrosis computed tomography (CFCT) scores. Results LCI was abnormal in 28 of 38 patients and a moderate correlation was observed between LCI and FEV₁ (r=−0.519, p=0.001). Moreover, LCI correlated well with CFCT total score (r=0.800, p<0.001) and also with subscores for airway wall thickening (r=0.809, p<0.001), mucus plugging (r=0.720, p<0.001) and bronchiectasis (r=0.494, p<0.001). Concordance was seen between LCI and CFCT in 25 of 30 (83%) patients, but between FEV₁ and CFCT in only 16 of 30 (53%) patients. LCI was more sensitive (90.9%, 95% CI 70.8 to 98.6) to detect patients with structural abnormalities than FEV₁ (36.4%, 95% CI 17.2 to 59.3). Conclusions We demonstrated that measuring LCI in patients with PCD is of clinical relevance; it was more frequently abnormal than FEV₁, correlated well with CFCT and was more sensitive than FEV₁ to detect patients with structural abnormalities.

Objectives To identify and summarise volatile organic compound (VOC) exposure profiles of healthcare occupations. Methods Personal (n=143) and mobile area (n=207) evacuated canisters were collected and analysed by a gas chromatograph/mass spectrometer to assess exposures to 14 VOCs among 14 healthcare occupations in five hospitals. Participants were volunteers identified by their supervisors. Summary statistics were calculated by occupation. Principal component analysis (PCA) was used to reduce the 14 analyte inputs to five orthogonal factors and identify occupations that were associated with these factors. Linear regressions were used to assess the association between personal and mobile area samples. Results Exposure profiles differed among occupations; ethanol had the highest geometric mean (GM) among nursing assistants (∼4900 and ∼1900 µg/m³, personal and area), and 2-propanol had the highest GM among medical equipment preparers (∼4600 and ∼2000 µg/m³, personal and area). The highest total personal VOC exposures were among nursing assistants (∼9200 µg/m³), licensed practical nurses (∼8700 µg/m³) and medical equipment preparers (∼7900 µg/m³). The influence of the PCA factors developed from personal exposure estimates varied by occupation, which enabled a comparative assessment of occupations. For example, factor 1, indicative of solvent use, was positively correlated with clinical laboratory and floor stripping/waxing occupations and tasks. Overall, a significant correlation was observed (r=0.88) between matched personal and mobile area samples, but varied considerably by analyte (r=0.23–0.64). Conclusions Healthcare workers are exposed to a variety of chemicals that vary with the activities and products used during activities. These VOC profiles are useful for estimating exposures for occupational hazard ranking for industrial hygienists as well as epidemiological studies.