The nasal epithelium plays a central role in modulating asthma, but this tissue is poorly represented in repositories such as GTEx, particularly for African-ancestry populations that are disproportionately affected by asthma. Using African-ancestry populations, we built and applied predictive models to estimate genetically driven gene expression in the nasal epithelium, and identified associations between predicted gene expression and asthma.
We trained gene expression prediction models using RNA-seq data generated from nasal epithelial samples and MEGA genotypes from 536 participants (253 asthma cases, 283 controls) of phase 2 of the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA). Using cross-validated elastic nets, we predicted gene expression from SNPs within a 1Mb window of each gene’s start and stop position, adjusting for sex, asthma, ancestry PC1, and 60 PEER factors. We used these models to predict nasal epithelial gene expression from TOPMed WGS available among 920 participants (426 asthma cases, 494 controls) of the Barbados Asthma Genetics Study (BAGS) and discovered transcriptome-wide associations (TWAS) with asthma using linear mixed models adjusted for sex, age, PC1, and kinship.
Out of 21,144 autosomal genes, 9,407 were significantly predicted from cis-SNPs (model R2>0.01 and P<0.05). From TWAS in BAGS, six genes were associated with asthma (q-value<0.1). Asthma cases had lower nasal epithelial expression of SCG3 (P=6E-5), UGGT1 (P=4E-5), TRIO (P=1E-5), and KPNA5 (P=2E-5), and higher expression of SORBS1 (P=5E-5) and UFD1 (P=2E-5). SCG3 is located in the 15q21 locus near asthma candidate genes RORA and SMAD3. None of the other five genes were identified in prior asthma GWAS; KPNA5 and SORBS1 were implicated in prior asthma expression studies. While SORBS1 encodes an adaptor protein primarily involved in insulin signaling, SORBS1 transcript usage has been shown to be higher in lung tissue of COPD cases compared to controls. The UGGT1-encoded protein glucosyltransferase 1 performs quality control of misfolded proteins in the endoplasmic reticulum (ER); its increased expression in the nasal airway may reflect ongoing ER stress characteristic of asthma.
Identification of expression signatures associated with asthma in the nasal epithelium recapitulated candidate asthma genes and identified novel candidate genes with biologically plausible mechanisms of action, providing new insight into the molecular mechanisms driving dysfunction in asthma.