Modification of the Association between PM(10) and Lung Function Decline by Cadherin 13 Polymorphisms in the SAPALDIA Cohort: A Genome-Wide Interaction Analysis

Background: Both air pollution and genetic variation have been shown to affect lung function. Their interaction has not been studied on a genome-wide scale to date. Objectives: We aimed to identify, in an agnostic fashion, genes that modify the association between long-term air pollution exposure and annual lung function decline in an adult population-based sample. Methods: A two-stage genome-wide interaction study was performed. The discovery (n = 763) and replication (n = 3,896) samples were derived from the multi-center SAPALDIA cohort (Swiss Cohort Study on Air Pollution and Lung Disease in Adults). Annual rate of decline in the forced mid-expiratory flow (FEF(25–75%)) was the main end point. Multivariate linear regression analyses were used to identify potential multiplicative interactions between genotypes and 11-year cumulative PM(10) exposure. Results: We identified a cluster of variants intronic to the CDH13 gene as the only locus with genome-wide significant interactions. The strongest interaction was observed for rs2325934 (p = 8.8 × 10(–10)). Replication of the interaction between this CDH13 variant and cumulative PM(10) exposure on annual decline in FEF(25–75%) was successful (p = 0.008). The interaction was not sensitive to adjustment for smoking or body weight. Conclusions: CDH13 is functionally linked to the adipokine adiponectin, an inflammatory regulator. Future studies need to confirm the interaction and assess how the result relates to previously observed interactions between air pollution and obesity on respiratory function. Citation: Imboden M, Kumar A, Curjuric I, Adam M, Thun GA, Haun M, Tsai MY, Pons M, Bettschart R, Turk A, Rochat T, Künzli N, Schindler C, Kronenberg F, Probst-Hensch NM. 2015. Modification of the association between PM(10) and lung function decline by cadherin 13 polymorphisms in the SAPALDIA cohort: a genome-wide interaction analysis. Environ Health Perspect 123:72–79; http://dx.doi.org/10.1289/ehp.1307398