Genetic risk score-informed re-evaluation of spirometry quality control to maximise power in epidemiological studies of lung function

Background and aimEpidemiological studies of lung function may discard one-third to one-half of participants due to spirometry measures deemed "low quality" using criteria adapted from clinical practice. We aimed to define new spirometry quality control (QC) criteria that optimise the signal-to-noise ratio in epidemiological studies of lung function. Material and methodsWe proposed a genetic risk score (GRS) informed strategy to categorize spirometer blows according to quality criteria. We constructed three GRSs comprised of SNPs associated with forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC) and the ratio of FEV1 to FVC (FEV1/FVC) in individuals from non-UK Biobank cohorts included in prior genome-wide association studies (GWAS). In the UK Biobank, we applied a step-wise testing of the GRS association across groups of spirometry blows stratified by acceptability flags to rank the blow quality. To reassess the QC criteria, we compared the genetic association results between analyses including different acceptability flags and applying different repeatability thresholds for spirometry measurements to determine the trade-off between sample size and measurement error. ResultsWe found that including blows previously excluded for cough, hesitation, excessive time to peak flow, or inadequate terminal plateau, and applying a repeatability threshold of 250ml, would maximise the statistical power for GWAS and retain acceptable precision in the UK Biobank. This approach allowed the inclusion of 29% more participants compared to the strictest ATS/ERS guidelines. ConclusionOur findings demonstrate the utility of GRS-informed QC to maximise the power of epidemiological studies for lung function traits.