A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure

Abstract

Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined ∼18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p < 5 × 10) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p < 5 × 10). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling (MSRA, EBF2).

Role of Rare and Low Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels

“…Studying gene-by-environment (G×E) interactions is important, as it extends our 42 knowledge of the genetic architecture of complex traits and improves our understanding of the 43 underlying mechanisms of common diseases for novel and known loci (22)(23)(24). Several large-44 scale genome-wide G×E studies have successfully identified novel common variants accounting 45 for the environmental effects such as alcohol consumption and smoking status on lipid levels and 46 other CVD related traits (25)(26)(27)(28)(29)(30)(31)(32)(33)(34). These studies have successfully identified common variant loci 47 that were not detected via analysis of main effects alone.…”

Multi-ethnic analysis shows genetic risk and environmental predictors interact to influence 25(OH)D concentration and optimal vitamin D intake

“…Two separate sets of models were investigated: 1) one-degree of freedom (DF) models which tested only the relevant interaction term and 2) 2-DF models which jointly tested both the relevant interaction term and the PGS main effect term (41). Relevant interaction terms were the PGS interacting with either vitamin D intake (PGS*intake) or available UV radiation (PGS*UV).…”

Large-scale multivariate multi-ancestry Interaction analyses point towards different genetic mechanisms by population and exposure

“…For each phenotype, a systematic genome-wide association study (GWAS) using the 1 degree of freedom (df) test for GxE interaction and the 2 df joint test of genetic and interaction effects 6 has been conducted. The results from these analyses have been published in four papers: SNP-by-alcohol interaction 7 and SNP-by-smoking interaction 8 on blood pressure, and SNP-by-alcohol interaction 9 and SNP-by-smoking interaction on lipids 10 .…”