Exonic variants associated with development of aspirin exacerbated respiratory diseases.

Abstract

Aspirin-exacerbated respiratory disease (AERD) is one phenotype of asthma, often

occurring in the form of a severe and sudden attack. Due to the time-consuming

nature and difficulty of oral aspirin challenge (OAC) for AERD diagnosis,

non-invasive biomarkers have been sought. The aim of this study was to identify

AERD-associated exonic SNPs and examine the diagnostic potential of a combination

of these candidate SNPs to predict AERD. DNA from 165 AERD patients, 397 subjects

with aspirin-tolerant asthma (ATA), and 398 normal controls were subjected to an

Exome BeadChip assay containing 240K SNPs. 1,023 models (210-1) were generated

from combinations of the top 10 SNPs, selected by the p-values in association

with AERD. The area under the curve (AUC) of the receiver operating

characteristic (ROC) curves was calculated for each model. SNP Function Portal

and PolyPhen-2 were used to validate the functional significance of candidate

SNPs. An exonic SNP, exm537513 in HLA-DPB1, showed the lowest p-value (p =

3.40x10-8) in its association with AERD risk. From the top 10 SNPs, a combination

model of 7 SNPs (exm537513, exm83523, exm1884673, exm538564, exm2264237,

exm396794, and exm791954) showed the best AUC of 0.75 (asymptotic p-value of

7.94x10-21), with 34% sensitivity and 93% specificity to discriminate AERD from

ATA. Amino acid changes due to exm83523 in CHIA were predicted to be "probably

damaging" to the structure and function of the protein, with a high score of '1'.

A combination model of seven SNPs may provide a useful, non-invasive genetic

marker combination for predicting AERD.