UC San Diego

Type 2 diabetes is a multifactorial disease that is the result of glycemic disfunction in the body. Risk for type 2 diabetes is influenced by the interplay of multiple lifestyle, environmental, and genetic factors. Prior genome wide association studies have identified hundreds of genetic variants associated with type 2 diabetes. However, the majority of these genetic studies have failed to consider the role of environmental risk factors on disease risk, e.g. gene x environment interaction analyses. The role of smoking as a modulator in the association between genetic variants and type 2 diabetes is of particular importance, since smoking is a modifiable risk factor and has been established as a causal risk factor for type 2 diabetes. Conducting a gene by smoking interaction analysis on type 2 diabetes allows consideration of both genetic and environmental risk factors and has the potential to unveil novel single-nucleotide polymorphisms (SNPs) that influence disease vulnerability typically missed by traditional analytic approaches. To conduct a large-scale gene x environment study, phenotypic and genotypic data on 345,955 individuals was utilized from 14 studies within two biomedical repositories, dbGaP and UK Biobank. Phenotypic data extracted from the studies were reviewed and harmonized prior to performing a gene by smoking genome-wide association study (GWAS) for each study. Individual GWAS statistics were combined through meta-analysis, stratified by racial/ethnic groups. This study included the following sample of individuals: 324,834 of European ancestry, 9,040 of African ancestry, 6,125 of Hispanic ancestry, and 5,956 of Asian ancestry. The study sample includes 40, 994 diabetics and 34,764 current smokers, and majority females (55%, 177,369). Results from the meta-analysis produced genome-wide significant SNPs for the European ancestry main effect and the Asian ancestry interaction effect. The European ancestry main effect results revealed a genome wide significant (p-value 9.59x10-33) signal in the TCF7L2 gene, a commonly replicated SNP in several GWAS’s of type 2 diabetes. The smoking by SNP results found SNPs at the genome-wide suggestive (p-value ≤1x10-5) level. The Asian ancestry interaction results revealed inflated results driven by two studies with modest sample size that we considered false positives, and therefore not included in the final results. This work underscores the importance of conducting gene by smoking interaction analyses on type 2 diabetes to identify genetic variants that influence disease vulnerability.