Diversity of CFTR variants across ancestries characterized using 454,727 UK biobank whole exome sequences.

BACKGROUND: Limited understanding of the diversity of variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene across ancestries hampers efforts to advance molecular diagnosis of cystic fibrosis (CF). The consequences pose a risk of delayed diagnoses and subsequently worsened health outcomes for patients. Therefore, characterizing the spectrum of CFTR variants across ancestries is critical for revolutionizing molecular diagnoses of CF. METHODS: We analyzed 454,727 UK Biobank (UKBB) whole-exome sequences to characterize the diversity of CFTR variants across ancestries. Using the PanUKBB classification, the participants were assigned into six major groups: African (AFR), American/American Admixed (AMR), Central South Asia (CSA), East Asian (EAS), European (EUR), and Middle East (MID). We segregated ancestry-specific CFTR variants, including those that are CF-causing or clinically relevant. The ages of certain CF-causing variants were determined and analyzed for selective pressure effects, and curated phenotype analysis was performed for participants with clinically relevant CFTR genotypes. RESULTS: We detected over 4000 CFTR variants, including novel ancestry-specific variants, across six ancestries. Europeans had the most unique CFTR variants [n = 2212], while the American group had the least unique variants [n = 23]. F508del was the most prevalent CF-causing variant found in all ancestries, except in EAS, where V520F was the most prevalent. Common EAS variants such as 3600G > A, V456A, and V520, which appeared approximately 270, 215, and 338 generations ago, respectively, did not show evidence of selective pressure. Sixteen participants had two CF-causing variants, with two being diagnosed with CF. We found 154 participants harboring a CF-causing and varying clinical consequences (VCC) variant. Phenotype analysis performed for participants with multiple clinically relevant variants returned significant associations with CF and its pulmonary phenotypes [Bonferroni-adjusted p < 0.05]. CONCLUSIONS: We leveraged the UKBB database to comprehensively characterize the broad spectrum of CFTR variants across ancestries. The detection of over 4000 CFTR variants, including several ancestry-specific and uncharacterized CFTR variants, warrants the need for further characterization of their functional and clinical relevance. Overall, the presentation of classical CF phenotypes seen in non-CF diagnosed participants with more than one CF-causing variant indicates that they may benefit from current CFTR modulator therapies.

Systematic single-variant and gene-based association testing of thousands of phenotypes in 394,841 UK Biobank exomes.

Genome-wide association studies have successfully discovered thousands of common variants associated with human diseases and traits, but the landscape of rare variations in human disease has not been explored at scale. Exome-sequencing studies of population biobanks provide an opportunity to systematically evaluate the impact of rare coding variations across a wide range of phenotypes to discover genes and allelic series relevant to human health and disease. Here, we present results from systematic association analyses of 4,529 phenotypes using single-variant and gene tests of 394,841 individuals in the UK Biobank with exome-sequence data. We find that the discovery of genetic associations is tightly linked to frequency and is correlated with metrics of deleteriousness and natural selection. We highlight biological findings elucidated by these data and release the dataset as a public resource alongside the Genebass browser for rapidly exploring rare-variant association results.