Evidence for Large-Scale Gene-by-Smoking Interaction Effects on Pulmonary Function

Background: Smoking is the strongest environmental risk factor for reduced pulmonary function. The genetic component of various pulmonary traits has also been demonstrated, and at least 26 loci have been reproducibly associated with either FEV1 (forced expiratory volume in 1 second) or FEV1/FVC (FEV1/forced vital capacity). Although the main effects of smoking and genetic loci are well established, the question of potential gene-by-smoking interaction effect remains unanswered. The aim of the present study was to assess, using a genetic risk score approach, whether the effect of these 26 loci on pulmonary function is influenced by smoking. Methods: We evaluated the interaction between smoking exposure, considered as either ever vs. never or pack-years, and a 26 SNPs genetic risk score in relation to FEV1 or FEV1/FVC in 50 047 participants of European ancestry from the CHARGE and SpiroMeta consortia. Results: We identified an interaction ( = −0.036, 95% confidence interval, -0.040 – -0.032, P=0.00057) between an unweighted 26 SNPs genetic risk score and smoking status (ever/never) on the FEV1/FVC ratio. In interpreting this interaction, we showed that the genetic risk of falling below the FEV1/FVC threshold used to diagnose chronic obstructive pulmonary disease is higher among ever smokers than among never smokers. Conclusions: This study highlights the benefit of using genetic risk scores for identifying interactions missed when studying individual SNPs, and shows for the first time that persons with the highest genetic risk for low FEV1/FVC may be more susceptible to the deleterious effects of smoking

Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function

Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways