Genetic Variants Associated with Gene Expression in the Lung and Asthma Susceptibility

Bérubé JC1, Lavoie-Charland E1, Gaudreault N1, Sbarra L1, Henry C1, Postma DS2, Sin DD3, Hao K4, Nickle DC5, Timens W2, Paré PD3, Laviolette M1, Boulet LP1 and Bossé Y1,6

1. Institut universitaire de cardiologie et de pneumologie de Québec, Quebec City, Canada; 2. University of Groningen, University Medical Center Groningen, GRIAC Research Institute, Groningen, Netherlands; 3. The University of British Columbia Centre for Heart Lung Innovation, St Paul’s Hospital, Vancouver, Canada; 4. Icahn School of Medicine at Mount Sinai, New York, NY, United States; 5. Merck & Co, MRL, Seattle, Washington, United States; 6. Department of Molecular Medicine, Laval University, Quebec City, Canada

Pathogenic changes occurring in airways of asthma patients generate chronic symptoms such as cough, shortness of breath, chest tightness and wheezing. Studying genetic regulation of lung transcriptome may lead to the identification of new variants associated with asthma susceptibility.

The top 160 SNPs associated with gene expression in the lung of 1,111 patients were selected and genotyped in 965 individuals of the Quebec City Case-Control Asthma Cohort. Allele frequencies were compared between asthma patients and controls.

Ten SNPs were found to be significantly associated with asthma (P <0.05). Rs17138154 on chromosome 7 was the SNP most strongly associated with asthma (P = 1.26E-03). The protective asthma allele was associated with lowered expression of LOC493754 in the lung (eQTL p value = 1.87E-45). The lung eQTL-SNP rs3807807 associated with the expression of ICA1 (eQTL p value = 1.84E-46) was also associated with asthma (P = 1.08E-02). In this case, the asthma risk allele showed less expression of ICA1 in the lung. Rs2249828, regulating the expression of PIGP in the lung (eQTL p value =4.18E-122), was also associated with asthma (P = 1.71E-02). Two SNPs in linkage disequilibrium with rs2249828 (rs2032088, r2 = 1.0; rs2835624, r2 = 0.92), showed an association with asthma in the meta-analysis of the European GABRIEL Consortium (P <0.05).

This project took advantage of a large-scale lung eQTL dataset to identify new functional genetic variants associated with asthma. The identification of lung eQTLs associated with asthma is not only elucidating new susceptibility genes, but also providing vital information about the genetic mechanisms leading to abnormal function of the genes that promote the development of the disease.