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

Abstract

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.

Keywords: CFTR; Cystic fibrosis; UK biobank; Whole exome sequencing.

Fig. 1

Most CFTR variants are intronic. Several variant types with varying consequences were identified in the CFTR gene. The labels in the chart represent the number and percentage of various variant types. Intronic variants (highlighted in orange) clearly dominated over half of the captured variants despite Whole Exome Sequencing technology capturing mostly exomes

Fig. 2

Ancestry-specific variants characterized. A) Graph of total number of variants (x-axis; Set Size) detected in each ancestry (y-axis). B) Intersection of variants detected across the ancestries. Each column corresponds to the number of variants in each intersection. Ancestries present in each intersection are represented by the black dots. Intersections with single dots represents ancestry-specific variants. C) A list of ancestry-specific variants. The highest number of unique CFTR variants (2212/3192) was detected in Europeans

Fig. 3

Common CF-causing variants in each ancestry represented in pie charts. For each ancestry, slices vary by color, with blue representing the most abundant CF-causing variant. F508del was the most common CF-causing variant detected in all ancestries, except for East Asia where V520F was the most common

Fig. 4

Ancestry-specific CF-causing variants characterized. A) Graph of total number of variants (x-axis; Set Size) detected in each ancestry (y-axis). B) Intersection of variants detected across the ancestries. Each column corresponds to the number of variants in each intersection. Ancestries present in each intersection are represented by the black dots. Intersections with single dots represents ancestry-specific CF-causing variants. C) A list of ancestry-specific CF-causing variants. The highest number of unique CF-causing variants (n=50) was detected in Europeans

Fig. 5

Classical CF phenotypes enriched in participants with >1 clinically relevant CFTR variant. A) Enriched phenotypes observed in patients with two CF-causing variants. B) Enriched phenotypes observed in patients with one CF-causing and a high impact variant. The top 10 enriched phenotypes are represented in bar graphs. The negative logarithm of the Bonferroni adjusted p-value was used to deduce the enrichment scores shown in the bars. Enrichment score >1.3 corresponds to a significance threshold of p<0.05